ES2984254T3 - Colorectal cancer screening - Google Patents

Abstract

The present disclosure provides, among other things, methods for detecting colorectal cancer (e.g., screening) and compositions related thereto. In various embodiments, the present disclosure provides methods for screening for colorectal cancer that include analyzing the methylation status of one or more methylation biomarkers, and compositions related thereto. In various embodiments, the present disclosure provides methods for detecting colorectal cancer (e.g., screening) that include detecting (e.g., screening) the methylation status of one or more methylation biomarkers in cfDNA, e.g., in ctDNA. In various embodiments, the present disclosure provides methods for screening for colorectal cancer that include detecting (e.g., screening) the methylation status of one or more methylation biomarkers in cfDNA, e.g., in ctDNA, using MSRE-qPCR.

Description

DESCRIPTION

Colorectal cancer screening

Background

Cancer screening is a critical component of cancer prevention, diagnosis, and treatment. Colorectal cancer (CRC) has been identified as the third most common type of cancer and the second most common cause of cancer mortality worldwide. There are reportedly more than 1.8 million new cases of colorectal cancer annually and approximately 881,000 colorectal cancer deaths, accounting for approximately 1 in 10 cancer deaths. Regular colorectal cancer screening is recommended, particularly for individuals over 50 years of age. Furthermore, the incidence of colorectal cancer in individuals under 50 years of age has increased over time. Statistical data suggest that current colorectal cancer screening techniques are inadequate.

Summary

Despite improvements over time, only approximately 40-44% of colorectal cancers are currently detected by screening at an early, localized stage. This is due, at least in part, to insufficient sensitivity and/or specificity of current screening techniques. Currently recommended techniques include colonoscopy and/or stool blood tests for people over 50 years of age.

Michail Galanopoulos et al: “Abnormal DNA methylation as a cell-free circulating DNA biomarker for colorectal cancer detection: A review of literature”, World Journal of Gastrointestinal Oncology, vol. 9, no. 4, 1 January 2017 (01/01/2017), page 142, XP055723984, ISSN:1984-5204, POI: 10.4251/wjgo.v9.i4.142, reviews the scientific literature regarding aberrant DNA methylation as a cell-free circulating DNA biomarker for colorectal cancer detection and presents several markers (Table 2) as well as combinations of markers to be tested together, however does not disclose the subject matter as encompassed by the wording of the claims. The present disclosure provides, as encompassed by the language of the claims, methods of screening for colorectal cancer and compositions related thereto. In various embodiments, the present disclosure provides, as encompassed by the language of the claims, methods of screening for colorectal cancer that include determining the methylation status (e.g., the number, frequency, or pattern of methylation) at one or more methylation sites found within a methylation locus, e.g., a differentially methylated region (DMR), of deoxyribonucleic acid (DNA) of a human subject, and compositions related thereto. In various embodiments, the present disclosure provides, as encompassed by the language of the claims, methods of screening for colorectal cancer that include examining the methylation status for each of one or more methylation loci in lncDNA (cell-free DNA), e.g., in tcDNA (circulating tumor DNA). In various embodiments, the present disclosure provides, as encompassed by the language of the claims, methods of screening for colorectal cancer that include determining a methylation status for each of one or more methylation loci in lncDNA, e.g., in tcDNA, using quantitative polymerase chain reaction (qPCR) (e.g., methylation-sensitive restriction enzyme quantitative polymerase chain reaction, MSRE-qPCR). Various compositions and methods provided herein, as encompassed by the language of the claims, provide sufficient sensitivity and specificity for clinical application in colorectal cancer screening. Various compositions and methods provided herein, as encompassed by the language of the claims, are useful in screening for colorectal cancer by analyzing an accessible tissue sample from a subject, e.g., a tissue sample that is blood or a blood component (e.g., lncDNA, e.g., tcDNA), or stool.

In one aspect, the invention relates, as encompassed by the wording of the claims, to a method of detecting (e.g., screening) colorectal cancer, the method comprising: determining a methylation status [e.g., a number, frequency, or pattern of methylation at one or more methylation sites within a methylation locus] for each of the following, in deoxyribonucleic acid (DNA) of a human subject: (a) a methylation locus [e.g., a differentially methylated region] within the ZNF132 gene; (b) a first methylation locus within the ADAMTS2 gene; and (c) a second methylation locus within the ADAMTS2 gene; and comparing the data obtained to reference values obtained from healthy individuals, and diagnosing colorectal cancer in the human subject if hypermethylation of the loci is detected, as compared to the reference sample.

In certain embodiments, the method further comprises determining a methylation status for each of the following, in the DNA of the human subject: (d) a methylation locus within the ZNF542 gene; and (e) a methylation locus within the LONRF2 gene.

In certain embodiments, the method further comprises determining a methylation status for a methylation locus within the ZNF492 gene in the DNA of the human subject.

In certain embodiments, the methylation locus within the ZNF132 gene comprises ZNF132' 415 (SEQ ID NO: 40).

In certain embodiments, the first methylation locus within the ADAMTS2 gene comprises ADAMTS2'254 (SEQ ID NO: 21).

In certain embodiments, the second methylation locus within the ADAMTS2 gene comprises ADAMTS2 '284 (SEQ ID NO: 22).

In certain embodiments, the methylation locus within the ZNF542 gene comprises ZNF542' 502 (SEQ ID NO: 35).

In certain embodiments, the methylation locus within the LONRF2 gene comprises LONRF2 '281 (SEQ ID NO: 19).

In certain embodiments, the methylation locus within the ZNF492 gene comprises ZNF492 '069 (SEQ ID NO: 42).

In certain embodiments, the DNA is isolated from blood or plasma of the human subject.

In certain embodiments, the DNA is cell-free DNA from the human subject.

In certain embodiments, methylation status is determined using quantitative polymerase chain reaction (qPCR) (e.g., methylation-sensitive restriction enzyme quantitative polymerase chain reaction, MSRE-qPCR).

In another aspect, the invention relates to a kit as encompassed by the wording of the claims for use in detecting (e.g., screening) colorectal cancer, the kit comprising: (a) an oligonucleotide primer pair for the amplification of a methylation locus within the ZNF132 gene; (b) an oligonucleotide primer pair for the amplification of a first methylation locus within the ADAMTS2 gene; and (c) an oligonucleotide primer pair for the amplification of a second methylation locus within the ADAMTS2 gene (e.g., and, optionally, the kit further comprising at least one methylation-sensitive restriction enzyme and/or a bisulfite reagent and a polymerase).

In certain embodiments, the kit further comprises: (d) an oligonucleotide primer pair for amplification of a methylation locus within the ZNF542 gene; and (e) an oligonucleotide primer pair for amplification of a methylation locus within the LONRF2 gene.

In certain embodiments, the kit further comprises: (f) a pair of oligonucleotide primers for amplification of a methylation locus within the ZNF492 gene.

In certain embodiments, (a) is an oligonucleotide primer pair for amplification of ZNF132'415 (primer pair SEQ ID NO: 91 and SEQ ID NO: 92).

In certain embodiments, (b) is an oligonucleotide primer pair for amplification of ADAMTS2'254 (primer pair SEQ ID NO: 53 and SEQ ID NO: 54).

In certain embodiments, (c) is an oligonucleotide primer pair for amplification of ADAMTS2 '284 (primer pair SEQ ID NO: 55 and SEQ ID NO: 56).

In certain embodiments, (d) is an oligonucleotide primer pair for amplification of ZNF542'502 (primer pair SEQ ID NO: 81 and SEQ ID NO: 82).

In certain embodiments, (e) is an oligonucleotide primer pair for amplification of LONRF2 '281 (primer pair SEQ ID NO: 49 and SEQ ID NO: 50).

In certain embodiments, (f) is an oligonucleotide primer pair for amplification of ZNF492 '069 (primer pair SEQ ID NO: 95 and SEQ ID NO: 96).

Definitions

A or an: The articles “a” and “an” are used herein to refer to one or more than one (i.e., at least one) of the grammatical objects of the article. As an example, “an item” refers to one item or more than one item.

Approximately: The term “approximately,” when used herein in reference to a value, refers to a value that is similar, in context, to the referenced value. In general, those skilled in the art, familiar with the context, will appreciate the relevant degree of variance encompassed by “approximately” in that context. For example, in some embodiments, e.g., as set forth herein, the term “approximately” may encompass a range of values that are within 25%, 20%, 19%, 18%, 17%, 16%, 15%, 14%, 13%, 12%, 11%, 10%, 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2%, 1%, or a fraction of a percent, of the referenced value.

Administration: As used herein, the term “administration” typically refers to the administration of a composition to a subject or system, for example to achieve delivery of an agent that is, is included in, or is otherwise delivered by, the composition.

Agent: As used herein, the term “agent” refers to an entity (e.g., a small molecule, peptide, polypeptide, nucleic acid, lipid, polysaccharide, complex, combination, mixture, system, or phenomenon such as heat, electric current, electric field, magnetic force, magnetic field, etc.).

Amelioration: As used herein, the term “amelioration” refers to the prevention, reduction, alleviation, or improvement of a condition of a subject. Amelioration includes, but does not require, complete recovery from or complete prevention of a disease, disorder, or condition.

Amplicon or amplicon molecule: As used herein, the term “amplicon” or “amplicon molecule” refers to a nucleic acid molecule generated by transcription from a template nucleic acid molecule, or a nucleic acid molecule having a sequence complementary thereto, or a double-stranded nucleic acid including any such nucleic acid molecule. Transcription may be initiated from a primer.

Amplification: As used herein, the term “amplification” refers to the use of a template nucleic acid molecule in combination with various reagents to generate additional nucleic acid molecules from the template nucleic acid molecule, which additional nucleic acid molecules may be identical or similar to (e.g., at least 70% identical, e.g., at least 75%, 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, or 100% identical to) a segment of the template nucleic acid molecule and/or a sequence complementary thereto.

Amplification Reaction Mixture: As used herein, the terms “amplification reaction mixture” or “amplification reaction” refer to a template nucleic acid molecule together with reagents sufficient for amplification of the template nucleic acid molecule.

Biological Sample: As used herein, the term “biological sample” typically refers to a sample obtained or derived from a biological source (e.g., a tissue or organism or cell culture) of interest, as described herein. In some embodiments, for example, as set forth herein, a biological source is or includes an organism, such as an animal or human. In some embodiments, for example, as set forth herein, a biological sample is or includes biological tissue or fluid. In some embodiments, for example, as set forth herein, a biological sample can be or include cells, tissue, or bodily fluid. In some embodiments, for example, as set forth herein, a biological sample may be or include blood, blood cells, cell-free DNA, free-floating nucleic acids, ascites, biopsy specimens, surgical specimens, body fluids containing cells, sputum, saliva, feces, urine, cerebrospinal fluid, peritoneal fluid, pleural fluid, lymph, gynecological fluids, secretions, excretions, skin smears, vaginal smears, oral smears, nasal swabs, rinses or washes such as ductal washes or bronchoalveolar lavages, aspirates, scrapings, bone marrow. In some embodiments, for example, as set forth herein, a biological sample is or includes cells obtained from a single subject or a plurality of subjects. A sample may be a “primary sample” obtained directly from a biological source, or it may be a “processed sample.” A biological sample may also be referred to as a “sample.”

Biomarker: As used herein, the term “biomarker,” consistent with its use in the art, refers to an entity whose presence, level, or form correlates with a particular biological event or condition of interest, such that it is considered to be a “marker” of that event or condition. Those skilled in the art will appreciate, for example, in the context of a DNA biomarker, that a biomarker may be or include a locus (such as one or more methylation loci) and/or the status of a locus (e.g., the status of one or more methylation loci). To give just a few examples of biomarkers, in some embodiments, for example, as set forth herein, a biomarker may be or include a marker for a particular disease, disorder, or condition, or it may be a marker of the qualitative or quantitative likelihood that a particular disease, disorder, or condition may develop, occur, or reoccur, for example, in a subject. In some embodiments, for example, as set forth herein, a biomarker may be or include a marker for a particular therapeutic outcome, or qualitative or quantitative likelihood thereof. Thus, in various embodiments, for example, as set forth herein, a biomarker may be predictive, prognostic, and/or diagnostic, of the relevant biological event or state of interest. A biomarker may be an entity of any chemical class. For example, in some embodiments, for example, as set forth herein, a biomarker may be or include a nucleic acid, a polypeptide, a lipid, a carbohydrate, a small molecule, an inorganic agent (e.g., a metal or ion), or a combination thereof. In some embodiments, for example, as set forth herein, a biomarker is a cell surface marker. In some embodiments, for example, as set forth herein, a biomarker is intracellular. In some embodiments, for example, as set forth herein, a biomarker is located outside of cells (e.g., secreted or otherwise generated or present outside of cells, e.g., in a bodily fluid such as blood, urine, tears, saliva, cerebrospinal fluid, and the like). In some embodiments, for example, as set forth herein, a biomarker is the methylation status of a methylation locus. In some cases, for example, as set forth herein, a biomarker may be referred to as a “marker.”

To give just one example of a biomarker, in some embodiments, e.g., as set forth herein, the term refers to the expression of a product encoded by a gene, the expression of which is characteristic of a particular tumor, tumor subclass, tumor stage, etc. Alternatively or additionally, in some embodiments, e.g., as set forth herein, the presence or level of a particular marker may be correlated with the activity (or level of activity) of a particular signaling pathway, e.g., a signaling pathway whose activity is characteristic of a particular class of tumors.

Those skilled in the art will appreciate that a biomarker may individually be a determinant of a particular biological event or state of interest, or may represent or contribute to a determination of the statistical likelihood of a particular biological event or state of interest. Those skilled in the art will appreciate that markers may differ in their specificity and/or sensitivity with respect to a particular biological event or state of interest.

Blood component: As used herein, the term “blood component” refers to any component of whole blood, including red blood cells, white blood cells, plasma, platelets, endothelial cells, mesothelial cells, epithelial cells, and cell-free DNA. Blood components also include plasma components, including proteins, metabolites, lipids, nucleic acids, and carbohydrates, and any other cells that may be present in blood, for example, due to pregnancy, organ transplantation, infection, injury, or disease.

Cancer: As used herein, the terms “cancer,” “malignant tumor,” “neoplasia,” “tumor,” and “carcinoma” are used interchangeably to refer to a disease, disorder, or condition in which cells exhibit or exhibited relatively abnormal, uncontrolled, and/or autonomous growth such that they exhibit or exhibited an abnormally elevated proliferation rate and/or aberrant growth phenotype. In some embodiments, for example, as set forth herein, a cancer may include one or more tumors. In some embodiments, for example, as set forth herein, a cancer may be or include cells that are precancerous (e.g., benign), malignant, premetastatic, metastatic, and/or non-metastatic. In some embodiments, for example, as set forth herein, a cancer may be or include a solid tumor. In some embodiments, for example, as set forth herein, a cancer may be or include a hematologic tumor. In general, examples of different types of cancers known in the art include, for example, colorectal cancer, hematopoietic cancers including leukemias, lymphomas (Hodgkin and non-Hodgkin), myelomas, and myeloproliferative disorders; sarcomas, melanomas, adenomas, solid tissue carcinomas, squamous cell carcinomas of the mouth, throat, larynx and lung, liver cancer, genitourinary cancers such as prostate, cervical, bladder, uterine and endometrial cancer and renal cell carcinomas, bone cancer, pancreatic cancer, skin cancer, cutaneous or intraocular melanoma, cancer of the endocrine system, cancer of the thyroid gland, cancer of the parathyroid gland, head and neck cancers, breast cancer, gastrointestinal cancers and cancers of the nervous system, benign lesions such as papillomas, and the like.

Chemotherapeutic Agent: As used herein, the term “chemotherapeutic agent,” consistent with its use in the art, refers to one or more agents that are known, or that have characteristics known, to treat or contribute to the treatment of cancer. In particular, chemotherapeutic agents include proapoptotic, cytostatic, and/or cytotoxic agents. In some embodiments, for example, as set forth herein, a chemotherapeutic agent can be or include alkylating agents, anthracyclines, cytoskeletal disruptors (e.g., microtubule targeting moieties such as taxanes, maytansine and analogs thereof, ofj, epothilones, histone deacetylase HDAC inhibitors), topoisomerase inhibitors (e.g., topoisomerase I and/or topoisomerase II inhibitors), kinase inhibitors, nucleotide analogs or nucleotide precursor analogs, peptide antibiotics, platinum-based agents, retinoids, vinca alkaloids, and/or analogs that share a relevant antiproliferative activity. In some particular embodiments, for example, as set forth herein, a chemotherapeutic agent may be or include actinomycin, all-trans-retinal acid, an aurisistatin, azacitidine, azathioprine, bleomycin, bortezomib, carboplatin, capecitabine, cisplatin, chlorambucil, cyclophosphamide, curcumin, cytarabine, daunorubicin, docetaxel, doxifluridine, doxorubicin, epirubicin, epothilone, etoposide, fluorouracil, gemcitabine, hydroxyurea, idarubicin, imatinib, irinotecan, maytansine and/or analogs thereof (e.g., DM1), mechlorethamine, mercaptopurine, methotrexate, mitoxantrone, a maytansinoid, oxaliplatin, paclitaxel, pemetrexed, teniposide, thioguanine, topotecan, valrubicin, vinblastine, vincristine, vindesine, vinorelbine, or a combination thereof. In some embodiments, for example, as set forth herein, a chemotherapeutic agent can be used in the context of an antibody-drug conjugate. In some embodiments, for example, as set forth herein, a chemotherapeutic agent is one found in an antibody-drug conjugate selected from the group consisting of: hLL1-doxorubicin, hRS7-SN-38, hMN-14-SN-38, hLL2-SN-38, hA20-SN-38, hPAM4-SN-38, hLL1-SN-38, hRS7-Pro-2-P-Dox, hMN-14-Pro-2-P-Dox, hLL2-Pro-2-P-Dox, hA20-Pro-2-P-Dox, hPAM4-Pro-2-P-Dox, hLL1-Pro-2-P-Dox, P4/D10-doxorubicin, gemtuzumab ozogamicin, brentuximab vedotin, trastuzumab emtansine, inotuzumabozogamicin, glembatumomab-vedotin, SAR3419, SAR566658, BIIB015, BT062, SGN-75, SGN-CD19A, AMG-172, AMG-595, BAY-94-9343, ASG-5ME, ASG-22ME, ASG-16M8F, MDX-1203, MLN-0264, anti-PSMAADC antibody, RG-7450, RG-7458, RG-7593, RG-7596, RG-7598, RG-7599, RG-7600, RG-7636, ABT-414, IMGN-853, IMGN-529, vorsetuzumab-mafodotin and lorvotuzumab-mertansine. In some embodiments, for example as set forth herein, a chemotherapeutic agent may be or comprise farnesyl-thiosalicylic acid (FTS), 4-(4-chloro-2-methylphenoxy)-N-hydroxybutanamide (CMH), estradiol (E2), tetramethoxystilbene (TMS), 6-tocatrienol, salinomycin, or curcumin.

Combination Therapy: As used herein, the term “combination therapy” refers to the administration to a subject of two or more agents or regimens such that the two or more agents or regimens together treat a disease, condition, or disorder of the subject. In some embodiments, for example, as set forth herein, the two or more therapeutic agents or regimens may be administered simultaneously, sequentially, or in overlapping dosing regimens. Those skilled in the art will appreciate that combination therapy includes, but does not require, that the two agents or regimens be administered together in a single composition, or at the same time.

Comparable: As used herein, the term “comparable” refers to members within sets of two or more conditions, circumstances, agents, entities, populations, etc., that may not be identical to one another but are sufficiently similar to permit comparison therebetween, such that one skilled in the art will appreciate that conclusions may reasonably be drawn based on observed differences or similarities. In some embodiments, for example, as set forth herein, comparable sets of conditions, circumstances, agents, entities, populations, etc., are typically characterized by a plurality of substantially identical characteristics and none, one, or a plurality of different characteristics. Those of ordinary skill in the art will understand, in context, what degree of identity is required to make members of a set comparable. For example, those of ordinary skill in the art will appreciate that members of sets of conditions, circumstances, agents, entities, populations, etc., are comparable to one another when they are characterized by a sufficient number and type of substantially identical characteristics to warrant a reasonable conclusion that observed differences can be attributed in whole or in part to non-identical characteristics thereof.

Detectable Moiety: The term “detectable moiety” as used herein refers to any element, molecule, functional group, compound, fragment, or other moiety that can be detected. In some embodiments, e.g., as set forth herein, a detectable moiety is provided or used alone. In some embodiments, e.g., as set forth herein, a detectable moiety is provided and/or used in association with (e.g., linked to) another agent. Examples of detectable moieties include, but are not limited to, various ligands, radionuclides (e.g., H, C, F, P, S, I, I, Cu, Re, In, Y, Tc, Lu, Zr, etc.), fluorescent dyes, chemiluminescent agents, bioluminescent agents, spectrally resolved inorganic fluorescent semiconductor nanocrystals (i.e., quantum dots), metal nanoparticles, nanoclusters, paramagnetic metal ions, enzymes, colorimetric labels, biotin, dioxygenin, haptens, and proteins for which antiserums or monoclonal antibodies are available.

Diagnosis: As used herein, the term “diagnosis” refers to determining whether, and/or the qualitative or quantitative likelihood that, a subject has or will develop a disease, disorder, condition, or state. For example, in diagnosing cancer, the diagnosis may include a determination regarding the risk, type, stage, malignancy, or other classification of a cancer. In some instances, for example, as set forth herein, a diagnosis may be or include a determination regarding the prognosis and/or likely response to one or more general or particular therapeutic agents or regimens.

Diagnostic Information: As used herein, the term “diagnostic information” refers to information useful in providing a diagnosis. Diagnostic information may include, but is not limited to, biomarker status information.

Differentially methylated: As used herein, the term “differentially methylated” describes a methylation site for which the methylation state differs between a first condition and a second condition. A methylation site that is differentially methylated can be said to be a differentially methylated site. In some cases, for example, as set forth herein, a DMR is defined by the amplicon produced by amplification using oligonucleotide primers, for example, a pair of oligonucleotide primers selected for amplification of the DMR or for amplification of a DNA region of interest present in the amplicon. In some cases, for example, as set forth herein, a DMR is defined as a region of DNA amplified by a pair of oligonucleotide primers, including the region having the sequence of, or a sequence complementary to, the oligonucleotide primers. In some instances, for example as set forth herein, a DMR is defined as a region of DNA amplified by a pair of oligonucleotide primers, excluding the region having the sequence of, or a sequence complementary to, the oligonucleotide primers. As used herein, a specifically provided DMR may be uniquely identified by the name of an associated gene followed by three digits of a start position, such that, for example, a DMR beginning at position 29921434 of ALK may be identified as ALK '434.

Differentially methylated region: As used herein, the term “differentially methylated region” (DMR) refers to a region of DNA that includes one or more differentially methylated sites. A DMR that includes an increased number or frequency of methylated sites in a selected condition of interest, such as a cancerous state, may be referred to as a hypermethylation DMR. A DMR that includes a decreased number or frequency of methylated sites in a selected condition of interest, such as a cancerous state, may be referred to as a hypomethylation DMR. A DMR that is a methylation biomarker for colorectal cancer may be referred to as a colorectal cancer DMR. In some cases, for example as set forth herein, a DMR may be a single nucleotide, which single nucleotide is a methylation site. In some cases, for example as set forth herein, a DMR is at least 10, at least 15, at least 20, at least 24, at least 50, or at least 75 base pairs in length. In some cases, for example as set forth herein, a DMR is less than 1000, less than 750, less than 500, less than 350, less than 300, or less than 250 base pairs in length (e.g., wherein the methylation status is determined using quantitative polymerase chain reaction (qPCR), e.g., methylation-sensitive restriction enzyme-quantitative polymerase chain reaction (MSRE-qPCR)). In some cases, for example as set forth herein, a DMR that is a methylation biomarker for detecting advanced adenoma may also be useful in identifying colorectal cancer.

DNA Region: As used herein, “DNA region” refers to any contiguous portion of a larger DNA molecule. Those skilled in the art will be familiar with techniques for determining whether a first DNA region and a second DNA region correspond, based on, for example, sequence similarity (e.g., sequence identity or homology) of the first and second DNA regions and/or context (e.g., nucleic acid sequence identity or homology in the 5' sense and/or 3' sense of the first and second DNA regions).

Unless otherwise specified herein, sequences found in or related to humans (e.g., that hybridize to human DNA) are found in, based on, and/or derived from the exemplary representative human genome sequence commonly referred to, and known to those skilled in the art as, the Homo sapiens (human) genome assembly GRCh38, hg38, and/or human genome reference consortium version 38. Those skilled in the art will further appreciate that regions of hg38 DNA may be named by a known system that includes identifying particular nucleotide positions or ranges thereof according to an assigned numbering.

Dosing Regimen: As used herein, the term “dosing regimen” can refer to a set of one or more of the same or different unit doses administered to a subject, typically including an administration of a plurality of unit doses each of which is separated from the administration of the others by a period of time. In various embodiments, for example, as set forth herein, one or more or all of the unit doses in a dosing regimen can be the same or can vary (e.g., increase over time, decrease over time, or adjust based on the subject and/or a medical professional's determination). In various embodiments, for example, as set forth herein, one or more or all of the time periods between each dose can be the same or can vary (e.g., increase over time, decrease over time, or adjust based on the subject and/or a medical professional's determination). In some embodiments, for example, as set forth herein, a given therapeutic agent has a recommended dosing regimen, which may involve one or more doses. Typically, at least one recommended dosing regimen of a marketed drug is known to those skilled in the art. In some embodiments, for example, as set forth herein, a dosing regimen is correlated with a desired or beneficial outcome when administered across a relevant population (i.e., is a therapeutic dosing regimen).

In the 3' direction: As used herein, the term “in the 3' direction” means that a first DNA region is closer, relative to a second DNA region, to the C-terminus of a nucleic acid that includes the first DNA region and the second DNA region.

Gene: As used herein, the term “gene” refers to a single region of DNA, e.g., on a chromosome, that includes a coding sequence encoding a product (e.g., an RNA product and/or a polypeptide product), together with all, some, or none of the DNA sequences that contribute to the regulation of expression of the coding sequence. In some embodiments, e.g., as set forth herein, a gene includes one or more non-coding sequences. In some particular embodiments, e.g., as set forth herein, a gene includes exonic and intronic sequences. In some embodiments, e.g., as set forth herein, a gene includes one or more regulatory elements that, e.g., may control or impact one or more aspects of gene expression (e.g., cell type-specific expression, inducible expression, etc.). In some embodiments, e.g., as set forth herein, a gene includes a promoter. In some embodiments, for example as set forth herein, a gene includes one or both of (i) DNA nucleotides extending a predetermined number of nucleotides upstream of the coding sequence and (ii) DNA nucleotides extending a predetermined number of nucleotides downstream of the coding sequence. In various embodiments, for example as set forth herein, the predetermined number of nucleotides may be 500 bp, 1 kb, 2 kb, 3 kb, 4 kb, 5 kb, 10 kb, 20 kb, 30 kb, 40 kb, 50 kb, 75 kb, or 100 kb.

Homology: As used herein, the term “homology” refers to the overall relationship between polymeric molecules, for example, between nucleic acid molecules (e.g., DNA molecules and/or RNA molecules) and/or between polypeptide molecules. Those skilled in the art will appreciate that homology can be defined, for example, by percent identity or by percent homology (sequence similarity). In some embodiments, for example, as set forth herein, polymeric molecules are considered to be “homologous” to one another if their sequences are at least 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, or 99% identical. In some embodiments, for example, as set forth herein, polymeric molecules are considered to be “homologous” to each other if their sequences are at least 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, or 99% similar.

Hybridize: As used herein, “hybridize” refers to the association of a first nucleic acid with a second nucleic acid to form a double-stranded structure, which association occurs by complementary pairing of nucleotides. Those skilled in the art will recognize that complementary sequences, among others, can hybridize. In various embodiments, for example, as set forth herein, hybridization can occur, for example, between nucleotide sequences that have a complementarity of at least 70%, for example, a complementarity of at least 75%, 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, or 100%. Those skilled in the art will further appreciate that whether or not hybridization of a first nucleic acid and a second nucleic acid occurs may depend on various reaction conditions. Conditions under which hybridization can occur are known in the art.

Hypomethylation: As used herein, the term “hypomethylation” refers to the state of a methylation locus having at least one less methylated nucleotide in a state of interest compared to a reference state (e.g., at least one less methylated nucleotide in colorectal cancer than in a healthy control).

Hypermethylation: As used herein, the term “hypermethylation” refers to the state of a methylation locus having at least one more methylated nucleotide in a state of interest compared to a reference state (e.g., at least one more methylated nucleotide in colorectal cancer than in healthy control).

Identity, Identical: As used herein, the terms “identity” and “identical” refer to the overall relationship between polymeric molecules, for example, between nucleic acid molecules (e.g., DNA molecules and/or RNA molecules) and/or between polypeptide molecules. Methods for calculating a percent identity such as between two given sequences are known in the art. Calculating the percent identity of two nucleic acid or polypeptide sequences, for example, can be performed by aligning the two sequences (or the complement of one or both sequences) for purposes of optimal comparison (e.g., gaps can be introduced into one or both of a first and second sequence for optimal alignment and non-identical sequences can be ignored for purposes of comparison). Nucleotides or amino acids at corresponding positions are then compared. When a position in the first sequence is occupied by the same residue (e.g., nucleotide or amino acid) as the corresponding position in the second sequence, then the molecules are identical at that position. The percent identity between two sequences is a function of the number of identical positions shared by the sequences and, optionally, taking into account the number of gaps and the length of each gap, which may need to be introduced for optimal alignment of the two sequences. Sequence comparison and determination of percent identity between two sequences can be accomplished using a computer algorithm, such as BLAST (Basic Local Alignment Search Tool).

“Improved,” “increased,” or “reduced”: As used herein, these terms, or grammatically comparable comparative terms, indicate values that are relative to a comparable reference measure. For example, in some embodiments, e.g., as set forth herein, an assessed value achieved with an agent of interest may be “improved” relative to that obtained with a comparable reference agent or no agent. Alternatively or additionally, in some embodiments, e.g., as set forth herein, an assessed value in a subject or system of interest may be “improved” relative to that obtained in the same subject or system under different conditions or at a different point in time (e.g., before or after an event such as administration of an agent of interest), or in a different comparable subject (e.g., in a comparable subject or system that differs from the subject or system of interest in the presence of one or more indicators of a particular disease, disorder, or condition of interest, or in prior exposure to a condition or agent, etc.). In some embodiments, for example, as set forth herein, comparative terms refer to statistically significant differences (e.g., differences of a prevalence and/or magnitude sufficient to achieve statistical significance). Those skilled in the art will know, or be able to readily determine, in a given context, a degree and/or prevalence of difference that is required or sufficient to achieve such statistical significance.

Methylation: As used herein, the term “methylation” includes methylation at any of (i) the C5 position of cytosine; (ii) the N4 position of cytosine; and (iii) the N6 position of adenine. Methylation also includes (iv) other types of nucleotide methylation. A nucleotide that is methylated may be referred to as a “methylated nucleotide” or a “methylated nucleotide base.” In certain embodiments, for example, as set forth herein, methylation specifically refers to methylation of cytosine residues. In some instances, methylation specifically refers to methylation of cytosine residues present at CpG sites.

Methylation assay: As used herein, the term “methylation assay” refers to any technique that can be used to determine the methylation status of a methylation locus.

Methylation Biomarker: As used herein, the term “methylation biomarker” refers to a biomarker that is or includes at least one methylation locus and/or the methylation status of at least one methylation locus, e.g., a hypermethylated locus. In particular, a methylation biomarker is a biomarker characterized by a change between a first state and a second state (e.g., between a cancerous state and a non-cancerous state) in the methylation status of one or more nucleic acid loci.

Methylation Locus: As used herein, the term “methylation locus” refers to a region of DNA that includes at least one differentially methylated region. A methylation locus that includes an increased number or frequency of methylated sites in a selected condition of interest, such as a cancerous state, may be referred to as a hypermethylated locus. A methylation locus that includes a decreased number or frequency of methylated sites in a selected condition of interest, such as a cancerous state, may be referred to as a hypomethylated locus. In some instances, for example as set forth herein, a methylation locus is at least 10, at least 15, at least 20, at least 24, at least 50, or at least 75 base pairs in length. In some cases, for example as set forth herein, a methylation locus is less than 1000, less than 750, less than 500, less than 350, less than 300, or less than 250 base pairs in length (e.g., where the methylation status is determined using quantitative polymerase chain reaction (qPCR), e.g., methylation-sensitive restriction enzyme-quantitative polymerase chain reaction (MSRE-qPCR)).

Methylation site: As used herein, a methylation site refers to a nucleotide or nucleotide position that is methylated under at least one condition. In its methylated state, a methylation site may be referred to as a methylated site.

Methylation status: As used herein, “methylation status,” “methylation state,” or “methylation profile” refers to the number, frequency, or pattern of methylation at methylation sites within a methylation locus. Accordingly, a change in methylation status between a first state and a second state may be or include an increase in the number, frequency, or pattern of methylated sites, or may be or include a decrease in the number, frequency, or pattern of methylated sites. In various instances, a change in methylation status is a change in methylation value.

Methylation Value: As used herein, the term “methylation value” refers to a numerical representation of a methylation state, e.g., in the form of a number representing the methylation frequency or ratio of a methylation locus. In some cases, e.g., as set forth herein, a methylation value can be generated by a method that includes quantifying the amount of intact nucleic acid present in a sample following restriction digestion of the sample with a methylation-dependent restriction enzyme. In some cases, e.g., as set forth herein, a methylation value can be generated by a method that includes comparing amplification profiles following a bisulfite reaction of a sample. In some cases, e.g., as set forth herein, a methylation value can be generated by comparing bisulfite-treated and untreated nucleic acid sequences. In some cases, for example as set forth herein, a methylation value is, includes, or is based on a quantitative PCR result.

Nucleic Acid: As used herein, in its broadest sense, the term “nucleic acid” refers to any compound and/or substance that is or can be incorporated into an oligonucleotide chain. In some embodiments, e.g., as set forth herein, a nucleic acid is a compound and/or substance that is or can be incorporated into an oligonucleotide chain via a phosphodiester linkage. As will be clear from context, in some embodiments, e.g., as set forth herein, the term nucleic acid refers to an individual nucleic acid residue (e.g., a nucleotide and/or nucleoside), and in some embodiments, e.g., as set forth herein, it refers to a polynucleotide chain comprising a plurality of individual nucleic acid residues. A nucleic acid may be or include DNA, RNA, or a combination thereof. A nucleic acid may include naturally occurring nucleic acid residues, nucleic acid analogs, and/or synthetic residues. In some embodiments, for example, as set forth herein, a nucleic acid includes naturally occurring nucleotides (e.g., adenosine, thymidine, guanosine, cytidine, uridine, deoxyadenosine, deoxythymidine, deoxyguanosine, and deoxycytidine). In some embodiments, for example, as set forth herein, a nucleic acid is or includes one or more nucleotide analogs (e.g., 2-aminoadenosine, 2-thiothymidine, inosine, pyrrolopyrimidine, 3-methyl-adenosine, 5-methylcytidine, C-5-propynyl-cytidine, C-5-propynyl-uridine, 2-aminoadenosine, C5-bromouridine, C5-fluorouridine, C5-iodouridine, C5-propynyl-uridine, C5-propynyl-cytidine, C5-methylcytidine, 2-aminoadenosine, 7-deazaadenosine, 7-deazaguanosine, 8-oxoadenosine, 8-oxoguanosine, 0(6)-methylguanine, 2-thiocytidine, methylated bases, intercalated bases, and combinations thereof).

In some embodiments, for example, as set forth herein, a nucleic acid has a nucleotide sequence that encodes a functional gene product such as an RNA or protein. In some embodiments, for example, as set forth herein, a nucleic acid includes one or more introns. In some embodiments, for example, as set forth herein, a nucleic acid includes one or more genes. In some embodiments, for example, as set forth herein, nucleic acids are prepared by one or more of isolation from a natural source, enzymatic synthesis by polymerization based on a complementary template (in vivo or in vitro), reproduction in a cell or recombinant system, and chemical synthesis.

In some embodiments, e.g., as set forth herein, a nucleic acid analog differs from a nucleic acid in that it does not use a phosphodiester backbone. For example, in some embodiments, e.g., as set forth herein, a nucleic acid may include one or more peptide nucleic acids, which are known in the art and have peptide bonds instead of phosphodiester bonds in the backbone. Alternatively or additionally, in some embodiments, e.g., as set forth herein, a nucleic acid has one or more phosphorothioate and/or 5'-N-phosphoramidite linkages instead of phosphodiester linkages. In some embodiments, e.g., as set forth herein, a nucleic acid comprises one or more modified sugars (e.g., 2'-fluororibose, ribose, 2'-deoxyribose, arabinose, and hexose) compared to those in naturally occurring nucleic acids.

In some embodiments, for example as set forth herein, a nucleic acid is or includes at least 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 20, 225, 250, 275, 300, 325, 350, 375, 400, 425, 450, 475, 500, 600, 700, 800, 900, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, 5000 or more residues. In some embodiments, for example, as set forth herein, a nucleic acid is partially or completely single-stranded, or partially or completely double-stranded.

Nucleic Acid Detection Assay: As used herein, the term “nucleic acid detection assay” refers to any method of determining the nucleotide composition of a nucleic acid of interest. Nucleic acid detection assays include, but are not limited to, DNA sequencing methods, polymerase chain reaction-based methods, probe hybridization methods, ligase chain reaction, etc.

Nucleotide: As used herein, the term “nucleotide” refers to a structural component, or structural element, of polynucleotides, e.g., DNA and/or RNA polymers. A nucleotide includes a base (e.g., adenine, thymine, uracil, guanine, or cytosine) and a sugar molecule and at least one phosphate group. As used herein, a nucleotide may be a methylated nucleotide or an unmethylated nucleotide.

Those skilled in the art will appreciate that nucleic acid terminology, such as, for example, “locus” or “nucleotide,” can refer to a locus or nucleotide of a single nucleic acid molecule and/or to the cumulative population of loci or nucleotides within a plurality of nucleic acids (e.g., a plurality of nucleic acids in a sample and/or representative of a subject) that are representative of the locus or nucleotide (e.g., having the same nucleic acid sequence and/or identical nucleic acid sequence context, or having a substantially identical nucleic acid sequence and/or nucleic acid context).

Oligonucleotide Primer: As used herein, the term oligonucleotide primer, or primer, refers to a nucleic acid molecule used, which can be used, or for use in, generating amplicons from a template nucleic acid molecule. Under conditions that permit transcription (e.g., in the presence of nucleotides and a DNA polymerase, and at a suitable temperature and pH), an oligonucleotide primer can provide a transcription initiation point from a template to which the oligonucleotide primer hybridizes. Typically, an oligonucleotide primer is a single-stranded nucleic acid between 5 and 200 nucleotides in length. Those skilled in the art will appreciate that the optimal primer length for generating amplicons from a template nucleic acid molecule can vary with conditions including temperature parameters, primer composition, and transcription or amplification method. An oligonucleotide primer pair, as used herein, refers to a set of two oligonucleotide primers that are respectively complementary to a first strand and a second strand of a template double-stranded nucleic acid molecule. The first and second members of an oligonucleotide primer pair may be referred to as a “forward” oligonucleotide primer and a “reverse” oligonucleotide primer, respectively, with respect to a template nucleic acid strand, since the forward oligonucleotide primer is capable of hybridizing to a nucleic acid strand complementary to the template nucleic acid strand, the reverse oligonucleotide primer is capable of hybridizing to the template nucleic acid strand, and the position of the forward oligonucleotide primer relative to the template nucleic acid strand is 5' of the position of the reverse oligonucleotide primer sequence relative to the template nucleic acid strand. Those skilled in the art will understand that the identification of a first and second oligonucleotide primers as forward and reverse oligonucleotide primers, respectively, is arbitrary insofar as these identifiers depend on whether a given nucleic acid strand or its complement is used as the template nucleic acid molecule.

Overlap: The term “overlap” is used herein to refer to two regions of DNA each containing a secondary sequence that is substantially identical to a secondary sequence of the same length in the other region (e.g., the two DNA regions have a common secondary sequence). “Substantially identical” means that the two secondary sequences of equal length differ by less than a given number of base pairs. In some cases, for example, as set forth herein, each secondary sequence is at least 20 base pairs in length that differ by less than 4, 3, 2, or 1 base pairs from each other (e.g., the two secondary sequences having at least 80%, at least 85%, at least 90%, at least 95% similarity, at least 97% similarity, at least 98% similarity, at least 99% similarity, or at least 99.5% similarity). In some cases, for example as set forth herein, each secondary sequence is at least 24 base pairs in length that differ by less than 5, 4, 3, 2, or 1 base pairs (e.g., with the two secondary sequences having at least 80%, at least 85%, at least 90%, at least 95% similarity, at least 97% similarity, at least 98% similarity, at least 99% similarity, or at least 99.5% similarity). In some cases, for example as set forth herein, each secondary sequence is at least 50 base pairs in length that differ by less than 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1 base pairs (e.g., with the two secondary sequences having at least 80%, at least 85%, at least 90%, at least 95% similarity, at least 97% similarity, at least 98% similarity, at least 99% similarity, or at least 99.5% similarity). In some cases, for example as set forth herein, each secondary sequence is at least 100 base pairs in length that differ by less than 20, 15, 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1 base pairs (e.g., with the two secondary sequences having at least 80%, at least 85%, at least 90%, at least 95% similarity, at least 97% similarity, at least 98% similarity, at least 99% similarity, or at least 99.5% similarity). In some cases, for example as set forth herein, each secondary sequence is at least 200 base pairs in length that differ by less than 40, 30, 20, 15, 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1 base pairs (e.g., the two secondary sequences having at least 80%, at least 85%, at least 90%, at least 95% similarity, at least 97% similarity, at least 98% similarity, at least 99% similarity, or at least 99.5% similarity). In some cases, for example as set forth herein, each secondary sequence is at least 250 base pairs in length that differ by less than 50, 40, 30, 20, 15, 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1 base pairs (e.g., with the two secondary sequences having at least 80%, at least 85%, at least 90%, at least 95% similarity, at least 97% similarity, at least 98% similarity, at least 99% similarity, or at least 99.5% similarity). In some cases, for example as set forth herein, each secondary sequence is at least 300 base pairs in length that differ by less than 60, 50, 40, 30, 20, 15, 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1 base pairs (e.g., with the two secondary sequences having at least 80%, at least 85%, at least 90%, at least 95% similarity, at least 97% similarity, at least 98% similarity, at least 99% similarity, or at least 99.5% similarity). In some cases, for example as set forth herein, each secondary sequence is at least 500 base pairs in length that differ by less than 100, 60, 50, 40, 30, 20, 15, 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1 base pairs (e.g., with the two secondary sequences having at least 80%, at least 85%, at least 90%, at least 95% similarity, at least 97% similarity, at least 98% similarity, at least 99% similarity, or at least 99.5% similarity). In some cases, for example as set forth herein, each secondary sequence is at least 1000 base pairs in length that differ by less than 200, 100, 60, 50, 40, 30, 20, 15, 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1 base pairs (e.g., with the two secondary sequences having at least 80%, at least 85%, at least 90%, at least 95% similarity, at least 97% similarity, at least 98% similarity, at least 99% similarity, or at least 99.5% similarity). In some cases, for example as set forth herein, the secondary sequence of a first region of the two DNA regions may comprise the entirety of the second region of the two DNA regions (or vice versa) (e.g., the common secondary sequence may contain the entirety of either or both regions).

Pharmaceutical Composition: As used herein, the term “pharmaceutical composition” refers to a composition in which an active agent is formulated together with one or more pharmaceutically acceptable carriers. In some embodiments, for example, as set forth herein, the active agent is present in a unit dosage amount appropriate for administration to a subject, for example, in a therapeutic regimen that exhibits a statistically significant likelihood of achieving a predetermined therapeutic effect when administered to a relevant population. In some embodiments, for example, as set forth herein, a pharmaceutical composition may be formulated for administration in a particular form (e.g., in a solid form or a liquid form) and/or may be specifically adapted, for example, for: oral administration (e.g., as an oral solution (aqueous or non-aqueous solutions or suspensions), tablet, capsule, bolus, powder, granule, paste, etc., which may be specifically formulated, for example, for buccal, sublingual, or systemic absorption); parenteral administration (e.g., by subcutaneous, intramuscular, intravenous, or epidural injection as, for example, a sterile solution or suspension, or sustained-release formulation, etc.); topical application (e.g., as a cream, ointment, patch, or spray applied, for example, to the skin, lungs, or oral cavity); intravaginal or intrarectal administration (e.g., as a vaginal suppository, cream, or foam); ocular administration; nasal or pulmonary administration, etc.

Pharmaceutically acceptable: As used herein, the term “pharmaceutically acceptable,” as applied to one or more, or all, of the component(s) for formulating a composition as disclosed herein, means that each component should be compatible with the other components of the composition and not be deleterious to the recipient thereof.

Pharmaceutically Acceptable Carrier: As used herein, the term “pharmaceutically acceptable carrier” refers to a pharmaceutically acceptable material, composition, or vehicle, such as a liquid or solid filler, diluent, excipient, or solvent-encapsulating material, that facilitates formulation and/or modifies the bioavailability of an agent, e.g., a pharmaceutical agent. Some examples of materials that may serve as pharmaceutically acceptable carriers include: sugars, such as lactose, glucose, and sucrose; starches, such as corn starch and potato starch; cellulose and its derivatives, such as sodium carboxymethylcellulose, ethylcellulose, and cellulose acetate; powdered gum tragacanth; malt; gelatin; talc; excipients, such as cocoa butter and suppository waxes; oils, such as peanut oil, cottonseed oil, safflower oil, sesame oil, olive oil, corn oil, and soybean oil; glycols, such as propylene glycol; polyols, such as glycerin, sorbitol, mannitol, and polyethylene glycol; esters, such as ethyl oleate and ethyl laurate; agar; buffering agents, such as magnesium hydroxide and aluminum hydroxide; alginic acid; pyrogen-free water; isotonic saline; Ringer's solution; ethyl alcohol; pH-buffered solutions; polyesters, polycarbonates, and/or polyanhydrides; and other nontoxic compatible substances used in pharmaceutical formulations.

Prevent or Prevention: The terms “prevent” and “prevention” as used herein in connection with the onset of a disease, disorder, or condition refer to reducing the risk of developing the disease, disorder, or condition; delaying the onset of the disease, disorder, or condition; delaying the onset of one or more features or symptoms of the disease, disorder, or condition; and/or reducing the frequency and/or intensity of one or more features or symptoms of the disease, disorder, or condition. Prevention may refer to prevention in a particular subject or to a statistical impact on a population of subjects. Prevention may be considered complete when the onset of a disease, disorder, or condition has been delayed for a predefined period of time.

Probe: As used herein, the term “probe” refers to a single- or double-stranded nucleic acid molecule that is capable of hybridizing to a complementary target and includes a detectable moiety. In certain embodiments, e.g., as set forth herein, a probe is a restriction digest product or is a synthetically produced nucleic acid, e.g., a nucleic acid produced by recombination or amplification. In some instances, e.g., as set forth herein, a probe is a capture probe useful in detecting, identifying, and/or isolating a target sequence, such as a gene sequence. In various instances, e.g., as set forth herein, a probe detectable moiety can be, e.g., an enzyme (e.g., ELISA, as well as enzyme-based histochemical assays), fluorescent moiety, radioactive moiety, or moiety associated with a luminescence signal.

Prognosis: As used herein, the term “prognosis” refers to determining the qualitative or quantitative likelihood of at least one possible future outcome or event. As used herein, a prognosis may be a determination of the likely course of a disease, disorder, or condition such as cancer in a subject, a determination concerning a subject's life expectancy, or a determination concerning response to therapy, e.g., to a particular therapy.

Prognostic Information: As used herein, the term “prognostic information” refers to information useful in providing a prognosis. Prognostic information may include, but is not limited to, biomarker status information.

Promoter: As used herein, a “promoter” may refer to a regulatory region of DNA that associates directly or indirectly (e.g., through promoter-bound proteins or substances) with an RNA polymerase and is involved in the initiation of transcription of a coding sequence.

Reference: As used herein, describes a standard or control against which a comparison is made. For example, in some embodiments, e.g., as set forth herein, an agent, subject, animal, individual, population, sample, sequence, or value of interest is compared to a reference or control agent, subject, animal, individual, population, sample, sequence, or value. In some embodiments, e.g., as set forth herein, a reference or characteristic thereof is tested and/or determined substantially simultaneously with the testing or determination of the characteristic in a sample of interest. In some embodiments, e.g., as set forth herein, a reference is a historical reference, optionally implemented in a tangible medium. Typically, as will be understood by those skilled in the art, a reference is determined or characterized under conditions or circumstances comparable to those being evaluated, e.g., with respect to a sample. Those skilled in the art will appreciate when there are sufficient similarities present to justify relying on, and/or comparing to, a particular possible reference or control.

Risk: As used herein with respect to a disease, disorder, or condition, the term “risk” refers to the qualitative or quantitative likelihood (whether expressed as a percentage or otherwise) that a particular individual will develop the disease, disorder, or condition. In some embodiments, for example, as set forth herein, risk is expressed as a percentage. In some embodiments, for example, as set forth herein, a risk is a qualitative or quantitative likelihood that is equal to or greater than 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, or 100%. In some embodiments, for example as set forth herein, risk is expressed as a qualitative or quantitative risk level relative to a reference risk or level or the risk of the same outcome attributed to a reference. In some embodiments, for example as set forth herein, the relative risk is increased or decreased compared to the reference sample by a factor of 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more.

Sample: As used herein, the term “sample” typically refers to an aliquot of material obtained or derived from a source of interest. In some embodiments, e.g., as set forth herein, a source of interest is a biological or environmental source. In some embodiments, e.g., as set forth herein, a sample is a “primary sample” obtained directly from a source of interest. In some embodiments, e.g., as set forth herein, as will be clear from the context, the term “sample” refers to a preparation that is obtained by processing a primary sample (e.g., by removing one or more components from, and/or adding one or more agents to, a primary sample). Such a “processed sample” may include, for example, cells, nucleic acids, or proteins extracted from a sample or obtained by subjecting a primary sample to techniques such as nucleic acid amplification or reverse transcription, isolation and/or purification of certain components, etc.

In some cases, for example, as set forth herein, a processed sample may be a DNA sample that has been amplified (e.g., pre-amplified). Thus, in various cases, for example, as set forth herein, an identified sample may refer to a primary form of the sample or a processed form of the sample. In some cases, for example, as set forth herein, a sample that is enzyme-digested DNA may refer to primary enzyme-digested DNA (the immediate product of enzymatic digestion) or to a further processed sample such as enzyme-digested DNA that has been subjected to an amplification step (e.g., an intermediate amplification step, e.g., pre-amplification) and/or a filtering step, purification step, or step that modifies the sample to facilitate an additional step, for example, in a method of determining methylation status (e.g., methylation status of a primary DNA sample and/or DNA as it exists in its original source context).

Screening: As used herein, the term “screening” refers to any method, technique, procedure, or task intended to generate diagnostic information and/or prognostic information. Accordingly, those skilled in the art will appreciate that the term screening encompasses a method, technique, procedure, or task that determines whether an individual has, is likely to have or develop, or is at risk of having or developing a disease, disorder, or condition, for example, colorectal cancer.

Specificity: As used herein, the “specificity” of a biomarker refers to the percentage of samples that are characterized by the absence of the event or state of interest for which the measurement of the biomarker accurately indicates the absence of the event or state of interest (true negative rate). In various embodiments, for example, as set forth herein, the characterization of negative samples is independent of the biomarker, and may be achieved by any relevant measurement, for example, any relevant measurement known to those skilled in the art. Thus, specificity reflects the likelihood that the biomarker will detect the absence of the event or state of interest when measured in a sample not characterized by that event or state of interest. In particular embodiments where the event or state of interest is colorectal cancer, for example, as set forth herein, specificity refers to the likelihood that a biomarker will detect the absence of colorectal cancer in a subject who lacks colorectal cancer. The absence of colorectal cancer can be determined, for example, by histology.

Sensitivity: As used herein, the “sensitivity” of a biomarker refers to the percentage of samples that are characterized by the presence of the event or condition of interest for which the measurement of the biomarker accurately indicates the presence of the event or condition of interest (true positive rate). In various embodiments, for example, as set forth herein, the characterization of positive samples is independent of the biomarker, and may be achieved by any relevant measurement, for example, any relevant measurement known to those skilled in the art. Thus, sensitivity reflects the likelihood that a biomarker will detect the presence of the event or condition of interest when measured in a sample characterized by the presence of that event or condition of interest. In particular embodiments where the event or condition of interest is colorectal cancer, for example, as set forth herein, sensitivity refers to the likelihood that a biomarker will detect the presence of colorectal cancer in a subject having colorectal cancer. The presence of colorectal cancer can be determined, for example, by histology.

Solid Tumor: As used herein, the term “solid tumor” refers to an abnormal mass of tissue that includes cancer cells. In various embodiments, for example, as set forth herein, a solid tumor is or includes an abnormal mass of tissue that does not contain cysts or fluid areas. In some embodiments, for example, as set forth herein, a solid tumor may be benign; in some embodiments, a solid tumor may be malignant. Examples of solid tumors include carcinomas, lymphomas, and sarcomas. In some embodiments, for example as set forth herein, solid tumors may be or include adrenal, bile duct, bladder, bone, brain, breast, cervix, colon, endometrium, esophagus, eye, gallbladder, gastrointestinal tract, kidney, larynx, liver, lung, nasal cavity, nasopharynx, oral cavity, ovaries, penis, pituitary gland, prostate, retina, salivary gland, skin, small intestine, stomach, testes, tumor, thyroid, uterine, vaginal, and/or vulvar tumors.

Cancer Stage: As used herein, the term “cancer stage” refers to a qualitative or quantitative assessment of the level of advancement of a cancer. In some embodiments, for example, as set forth herein, the criteria used to determine the stage of a cancer may include, but are not limited to, one or more of where the cancer is located in the body, tumor size, whether the cancer has spread to lymph nodes, whether the cancer has spread to one or more other parts of the body, etc. In some embodiments, for example, as set forth herein, cancer may be staged using the so-called TNM system, whereby T refers to the size and extent of the main tumor, commonly referred to as the primary tumor; N refers to the number of nearby lymph nodes that have cancer; and M refers to whether the cancer has metastasized. In some embodiments, for example, as set forth herein, a cancer may be referred to as stage 0 (abnormal cells are present but have not spread to nearby tissue, also referred to as carcinoma in situ, or CIS; CIS is not cancer, but can become cancer), stage I-III (cancer is present; the higher the number, the larger the tumor and the more it has spread to nearby tissues), or stage IV (cancer has spread to distant parts of the body). In some embodiments, for example, as set forth herein, a cancer may be assigned to a stage selected from the group consisting of: in situ (abnormal cells are present but have not spread to nearby tissue); localized (cancer is limited to the site where it started, with no signs of having spread); regional (cancer has spread to nearby lymph nodes, tissues, or organs); distant (cancer has spread to distant parts of the body); and unknown (there is not enough information to identify the stage of the cancer).

Prone to: An individual who is “prone to” a disease, disorder, or condition is at risk of developing the disease, disorder, or condition. In some embodiments, for example, as set forth herein, an individual who is prone to a disease, disorder, or condition does not exhibit any symptoms of the disease, disorder, or condition. In some embodiments, for example, as set forth herein, an individual who is prone to a disease, disorder, or condition has not been diagnosed with the disease, disorder, and/or condition. In some embodiments, for example, as set forth herein, an individual who is prone to a disease, disorder, or condition is an individual who has been exposed to conditions associated with, or exhibits a biomarker status (e.g., a methylation status) associated with, the development of the disease, disorder, or condition. In some embodiments, for example, as set forth herein, a risk of developing a disease, disorder, and/or condition is a population-based risk (e.g., family members of individuals suffering from the disease, disorder, or condition).

Subject: As used herein, the term “subject” refers to an organism, typically a mammal (e.g., a human). In some embodiments, e.g., as set forth herein, a subject is suffering from a disease, disorder, or condition. In some embodiments, e.g., as set forth herein, a subject is prone to a disease, disorder, or condition. In some embodiments, e.g., as set forth herein, a subject exhibits one or more symptoms or characteristics of a disease, disorder, or condition. In some embodiments, e.g., as set forth herein, a subject is not suffering from a disease, disorder, or condition. In some embodiments, e.g., as set forth herein, a subject does not exhibit any symptoms or characteristics of a disease, disorder, or condition. In some embodiments, e.g., as set forth herein, a subject is someone with one or more characteristic traits of a propensity for, or risk of, a disease, disorder, or condition. In some embodiments, for example, as set forth herein, a subject is a patient. In some embodiments, for example, as set forth herein, a subject is an individual who has been diagnosed and/or administered a therapy. In some instances, for example, as set forth herein, a human subject may be interchangeably referred to as an “individual.”

Therapeutic Agent: As used herein, the term “therapeutic agent” refers to any agent that elicits a desired pharmacological effect when administered to a subject. In some embodiments, e.g., as set forth herein, an agent is considered to be a therapeutic agent if it demonstrates a statistically significant effect across an appropriate population. In some embodiments, e.g., as set forth herein, the appropriate population may be a model organism population or a human population. In some embodiments, e.g., as set forth herein, an appropriate population may be defined by various criteria, such as a certain age group, sex, genetic background, pre-existing clinical conditions, etc. In some embodiments, e.g., as set forth herein, a therapeutic agent is a substance that can be used for the treatment of a disease, disorder, or condition. In some embodiments, for example, as set forth herein, a therapeutic agent is an agent that has been approved or is required to be approved by a government agency before it can be marketed for administration to humans. In some embodiments, for example, as set forth herein, a therapeutic agent is an agent for which a prescription is required for administration to humans.

Therapeutically Effective Amount: As used herein, the term “therapeutically effective amount” refers to an amount that produces a desired effect for which it is administered. In some embodiments, for example, as set forth herein, the term refers to an amount that is sufficient, when administered to a population suffering from or prone to a disease, disorder, or condition, according to a therapeutic dosing regimen, to treat the disease, disorder, or condition. Those of ordinary skill in the art will appreciate that the term therapeutically effective amount does not in fact require that successful treatment be achieved in a particular individual. Rather, a therapeutically effective amount can be an amount that provides a particular desired pharmacological response in a significant number of subjects when administered to individuals in need of such treatment. In some embodiments, for example, as set forth herein, reference to a therapeutically effective amount may be a reference to an amount as measured in one or more specific tissues (e.g., a tissue affected by the disease, disorder, or condition) or fluids (e.g., blood, saliva, serum, sweat, tears, urine, etc.). Those of ordinary skill in the art will appreciate that, in some embodiments, a therapeutically effective amount of a particular agent may be formulated and/or administered in a single dose. In some embodiments, for example, as set forth herein, a therapeutically effective agent may be formulated and/or administered in a plurality of doses, for example, as part of a multiple-dose dosing regimen.

Treatment: As used herein, the term “treatment” (also “treating” or “treating”) refers to the administration of a therapy that, partially or completely, alleviates, ameliorates, mitigates, inhibits, delays the onset of, reduces the intensity of, and/or reduces the incidence of one or more symptoms, features, and/or causes of a particular disease, disorder, or condition, or is administered for the purpose of achieving any such results. In some embodiments, for example, as set forth herein, such treatment may be of a subject who does not show any signs of the relevant disease, disorder, or condition and/or of a subject who only shows initial signs of the relevant disease, disorder, or condition. Alternatively or additionally, such treatment may be of a subject who shows one or more established signs of the relevant disease, disorder, and/or condition. In some embodiments, for example, as set forth herein, treatment may be of a subject who has been diagnosed as having the relevant disease, disorder, and/or condition. In some embodiments, for example, as set forth herein, the treatment may be of a subject known to have one or more propensity factors that are statistically correlated with an increased risk of developing the relevant disease, disorder, or condition. In various examples, the treatment is of a cancer.

In the 5' direction: As used herein, the term “in the 5' direction” means that a first DNA region is closer, relative to a second DNA region, to the N-terminus of a nucleic acid that includes the first DNA region and the second DNA region.

Unit Dose: As used herein, the term “unit dose” refers to an amount administered as a single dose and/or in a physically discrete unit of a pharmaceutical composition. In many embodiments, e.g., as set forth herein, a unit dose contains a predetermined amount of an active agent. In some embodiments, e.g., as set forth herein, a unit dose contains a single, entire dose of the agent. In some embodiments, e.g., as set forth herein, more than one unit dose is administered to achieve a single total dose. In some embodiments, e.g., as set forth herein, administration of multiple unit doses is required, or is expected to be required, in order to achieve an intended effect. A unit dose may be, for example, a volume of liquid (e.g., an acceptable carrier) containing a predetermined amount of one or more therapeutic moieties, a predetermined amount of one or more therapeutic moieties in solid form, a sustained release formulation or drug delivery device containing a predetermined amount of one or more therapeutic moieties, etc. It will be appreciated that a unit dose may be present in a formulation that includes any of a variety of components in addition to the therapeutic agent(s). For example, acceptable carriers (e.g., pharmaceutically acceptable carriers), diluents, stabilizers, buffers, preservatives, etc. may be included. Those skilled in the art will appreciate that, in many embodiments, for example, as set forth herein, a total appropriate daily dosage of a particular therapeutic agent may comprise a portion, or a plurality, of unit doses, and may be decided, for example, by a medical professional within the scope of reasonable medical judgment. In some embodiments, for example, as set forth herein, the specific effective dosage level for any particular subject or organism may depend upon a variety of factors including the disorder being treated and the intensity of the disorder; activity of the specific active compound employed; specific composition employed; age, body weight, general health, sex, and diet of the subject; time of administration, and rate of excretion of the specific active compound employed; duration of treatment; additional drugs and/or therapies used in combination or simultaneously with the specific compound(s) employed; and similar factors well known in the medical arts.

Unmethylated: As used herein, the terms “unmethylated” and “unmethylated” are used interchangeably and mean that an identified DNA region does not include any methylated nucleotides.

Variant: As used herein, the term “variant” refers to an entity that exhibits significant structural identity to a reference entity but differs structurally from the reference entity in terms of the presence, absence, or level of one or more chemical moieties as compared to the reference entity. In some embodiments, for example, as set forth herein, a variant also functionally differs from its reference entity. In general, whether a particular entity is appropriately considered to be a “variant” of a reference entity is based on its degree of structural identity to the reference entity. A variant may be a molecule comparable to, but not identical to, a reference. For example, a variant nucleic acid may differ from a reference nucleic acid by one or more differences in nucleotide sequence. In some embodiments, for example as set forth herein, a variant nucleic acid exhibits an overall sequence identity to a reference nucleic acid that is at least 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, or 99%. In many embodiments, for example as set forth herein, a nucleic acid of interest is considered to be a “variant” of a reference nucleic acid if the nucleic acid of interest has a sequence that is identical to that of the reference except for a small number of sequence alterations at particular positions. In some embodiments, for example as set forth herein, a variant has 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1 substituted residues compared to a reference. In some embodiments, for example as set forth herein, a variant has no more than 5, 4, 3, 2, or 1 residue additions, substitutions, or deletions compared to the reference. In various embodiments, for example as set forth herein, the number of additions, substitutions, or deletions is less than about 25, about 20, about 19, about 18, about 17, about 16, about 15, about 14, about 13, about 10, about 9, about 8, about 7, about 6, and typically there are less than about 5, about 4, about 3, or about 2 residues.

Brief description of the drawings

The foregoing and other objects, aspects, features and advantages of the present disclosure will become more apparent and better understood by reference to the following description taken in conjunction with the accompanying drawings, in which:

Figure 1 is a schematic showing an example MSRE-qPCR approach.

Figure 2 is a table showing characteristics of a first group of 70 human subjects. Figure 2 provides the percentage of women, percentage of men, age range, and BMI of subjects. Figure 2 further distinguishes the types of colorectal cancer identified in the first group of subjects as localized or advanced based on histologic evaluation, and as proximal or distal based on colonoscopy evaluation of the colon.

Figure 3 is a table showing characteristics of a second group of 63 human subjects. Figure 3 provides the percentage of women, percentage of men, age range, and BMI of subjects. Figure 3 further distinguishes the types of colorectal cancer identified in the second group of subjects as localized or advanced based on histologic evaluation, and as proximal or distal based on colonoscopy evaluation of the colon.

Figure 4 includes panels A and B. Panel A of Figure 4 is a graph showing the colorectal cancer screening performance using a representative proof-of-concept panel from DMR in the second subject group. The ROC curve and AUC are shown for all subjects in the second subject group. Panel B of Figure 4 is a diagram showing accuracy values, including, from left to right, the overall sensitivity of colorectal screening for detecting colorectal cancer, sensitivity of colorectal screening for detecting localized colorectal cancer, sensitivity of colorectal screening for detecting advanced colorectal cancer, sensitivity of colorectal screening for detecting proximal colorectal cancer, sensitivity of colorectal screening for detecting distal colorectal cancer, and specificity of colorectal screening for control subjects (healthy subjects and subjects with non-advanced adenoma).

Figure 5 is a graph depicting Ct values from MSRE-qPCR of ALK '434 for subjects with colorectal cancer and control subjects (healthy subjects and subjects with non-advanced adenoma). The data represent the second group of subjects (63 subjects) used for testing. For presentation purposes, Ct values are subtracted from 45 (45 - Ct). Values of 45 - Ct correspond to a higher methylation status, demonstrating hypermethylation in subjects with colorectal cancer.

Figure 6 is a graph depicting Ct values from MSRE-qPCR of FGF14 '577 DMR for subjects with colorectal cancer and control subjects (healthy subjects and subjects with non-advanced adenoma). The data represent the second group of subjects (63 subjects) used for testing. For presentation purposes, Ct values are subtracted from 45 (45 - Ct). Values of 45 - Ct correspond to a higher methylation status, demonstrating hypermethylation in subjects with colorectal cancer.

Figure 7 is a graph depicting Ct values from MSRE-qPCR of PDGFD '388 for subjects with colorectal cancer and control subjects (healthy subjects and subjects with non-advanced adenoma). The data represent the second group of subjects (63 subjects) used for testing. For presentation purposes, Ct values are subtracted from 45 (45 - Ct). Values of 45 - Ct correspond to a higher methylation status, demonstrating hypermethylation in subjects with colorectal cancer.

Figure 8 is a graph depicting Ct values from MSRE-qPCR of JAM2 '320 for subjects with colorectal cancer and control subjects (healthy subjects and subjects with non-advanced adenoma). The data represent the second group of subjects (63 subjects) used for testing. For presentation purposes, Ct values are subtracted from 45 (45 - Ct). Values of 45 - Ct correspond to a higher methylation status, demonstrating hypermethylation in subjects with colorectal cancer.

Figure 9 is a graph depicting Ct values from MSRE-qPCR of LONRF2 '281 for subjects with colorectal cancer and control subjects (healthy subjects and subjects with non-advanced adenoma). The data represent the second group of subjects (63 subjects) used for testing. For presentation purposes, Ct values are subtracted from 45 (45 - Ct). Values of 45 - Ct correspond to a higher methylation status, demonstrating hypermethylation in subjects with colorectal cancer.

Figure 10 is a table showing characteristics of a third subject group of 82 human subjects. Figure 10 provides the percentage of women, percentage of men, age range, and BMI of subjects diagnosed by screening using 28 colorectal cancer DMRs of the present disclosure. Figure 10 further distinguishes the types of colorectal cancer identified in the third subject group as localized or advanced based on histologic evaluation, and as proximal or distal based on colonoscopy evaluation of the colon.

Figure 11 is a graph showing the colorectal cancer screening performance using a 28 DMR panel in the third subject group. The ROC curve and AUC are shown for all subjects in the third subject group. The ROC curve analysis showed that a 28<d>M<r> panel achieved an overall colorectal cancer sensitivity of 79%, with a sensitivity of 75% for localized (early) cancer and a sensitivity of 84% for advanced cancer, with a very stable specificity of 87% at an AUC of 82% (see also Table 15).

Figure 12 is a graph depicting Ct values from MSRE-qPCR of ZNF471'527 for subjects with colorectal cancer and control subjects (healthy subjects and subjects with non-advanced adenoma). The data represent the third group of subjects (82 subjects). For presentation purposes, Ct values are subtracted from 45 (45 - Ct). Values of 45 - Ct correspond to a higher methylation status, demonstrating hypermethylation in subjects with colorectal cancer.

Figure 13 is a graph depicting Ct values from MSRE-qPCR of FGF14 '577 for subjects with colorectal cancer and control subjects (healthy subjects and subjects with non-advanced adenoma). The data represent the third group of subjects (82 subjects). For presentation purposes, Ct values are subtracted from 45 (45 - Ct). Values of 45 - Ct correspond to a higher methylation status, demonstrating hypermethylation in subjects with colorectal cancer.

Figure 14 is a graph depicting Ct values from MSRE-qPCR of PDGFD '388 for subjects with colorectal cancer and control subjects (healthy subjects and subjects with non-advanced adenoma). The data represent the third group of subjects (82 subjects). For presentation purposes, Ct values are subtracted from 45 (45 - Ct). Values of 45 - Ct correspond to a higher methylation status, demonstrating hypermethylation in subjects with colorectal cancer.

Figure 15 is a graph depicting Ct values from MSRE-qPCR of ADAMTS2 '254 for subjects with colorectal cancer and control subjects (healthy subjects and subjects with non-advanced adenoma). The data represent the third group of subjects (82 subjects). For presentation purposes, Ct values are subtracted from 45 (45 - Ct). Values of 45 - Ct correspond to a higher methylation status, demonstrating hypermethylation in subjects with colorectal cancer.

Figure 16 is a graph depicting Ct values from MSRE-qPCR of ZNF471 '558 (DMR alternatively referred to herein as ZNF471_2) for colorectal cancer subjects and control subjects (healthy subjects and subjects with non-advanced adenoma). The data represent the third group of subjects (82 subjects). For presentation purposes, Ct values are subtracted from 45 (45 - Ct). Values of 45 - Ct correspond to a higher methylation status, demonstrating hypermethylation in colorectal cancer subjects.

Figure 17 is a graph depicting Ct values from MSRE-qPCR of ST6GALNAC5 '456 for subjects with colorectal cancer and control subjects (healthy subjects and subjects with non-advanced adenoma). The data represent the third group of subjects (82 subjects). For presentation purposes, Ct values are subtracted from 45 (45 - Ct). Values of 45 - Ct correspond to a higher methylation status, demonstrating hypermethylation in subjects with colorectal cancer.

Figure 18 is a graph depicting Ct values from MSRE-qPCR of ZNF542'525 for subjects with colorectal cancer and control subjects (healthy subjects and subjects with non-advanced adenoma). The data represent the third group of subjects (82 subjects). For presentation purposes, Ct values are subtracted from 45 (45-Ct). Values of 45 - Ct correspond to a higher methylation status, demonstrating hypermethylation in subjects with colorectal cancer.

Figure 19 is a graph depicting Ct values from MSRE-qPCR of LONRF2 '281 for subjects with colorectal cancer and control subjects (healthy subjects and subjects with non-advanced adenoma). The data represent the third group of subjects (82 subjects). For presentation purposes, Ct values are subtracted from 45 (45 - Ct). Values of 45 - Ct correspond to a higher methylation status, demonstrating hypermethylation in subjects with colorectal cancer.

Figure 20 is a schematic showing example methylation changes in methylation status between normal and cancer cells, and further indicating how changes in methylation status may impact gene expression differences between normal and cancer cells.

Figure 21 is a table showing the characteristics of a subject group of 215 subjects used as a training set. Figure 21 provides the number of females, number of males, age range, and colorectal cancer status of the subjects. Figure 21 further distinguishes the types of colorectal cancer identified in those with colorectal cancer in the subject group as localized or advanced based on histologic evaluation, and as proximal or distal based on colonoscopy evaluation of the colon.

Figure 22 is a table showing the characteristics of a fourth subject group of 774 subjects used as a validation set. Figure 22 provides the number of females, number of males, age range, and cancer status of the subjects. Figure 22 further distinguishes the types of cancer identified in those with cancer in the subject group as localized or advanced based on histological evaluation.

Figure 23 is a graph showing the performance of a 3-marker panel for colorectal cancer screening using DMR from Table 18. The ROC curve and performance characteristics are shown for all subjects in the fourth validation subject group.

Figure 24 is a graph showing the performance of a 5-marker panel for colorectal cancer screening using DMR from Table 19. The ROC curve and performance characteristics are shown for all subjects in the fourth validation subject group.

Figure 25 is a graph showing the performance of a 6-marker panel for colorectal cancer screening using DMR from Table 20. The ROC curve and performance characteristics are shown for all subjects in the fourth validation subject group.

Figure 26 is a graph depicting Ct values from MSRE-qPCR of ZNF132'415 for subjects with colorectal cancer and control subjects (healthy subjects, subjects with non-advanced adenoma, and subjects with other cancers). The data represent the fourth group of subjects (774 subjects). For presentation purposes, Ct values are subtracted from 45 (45 - Ct). Values of 45 - Ct correspond to a higher methylation status, demonstrating hypermethylation in subjects with colorectal cancer.

Figure 27 is a graph depicting Ct values from MSRE-qPCR of ADAMTS2 '254 for subjects with colorectal cancer and control subjects (healthy subjects, subjects with non-advanced adenoma, and subjects with other cancers). The data represent the fourth group of subjects (774 subjects). For presentation purposes, Ct values are subtracted from 45 (45 - Ct). Values of 45 - Ct correspond to a higher methylation status, demonstrating hypermethylation in subjects with colorectal cancer.

Figure 28 is a graph depicting Ct values from MSRE-qPCR of ADAMTS2 '284 for subjects with colorectal cancer and control subjects (healthy subjects, subjects with non-advanced adenoma, and subjects with other cancers). The data represent the fourth group of subjects (774 subjects). For presentation purposes, Ct values are subtracted from 45 (45 - Ct). Values of 45 - Ct correspond to a higher methylation status, demonstrating hypermethylation in subjects with colorectal cancer.

Figure 29 is a graph depicting Ct values from MSRE-qPCR of ZNF542 '502 for subjects with colorectal cancer and control subjects (healthy subjects, subjects with non-advanced adenoma, and subjects with other cancers). The data represent the fourth group of subjects (774 subjects). For presentation purposes, Ct values are subtracted from 45 (45 - Ct). Values of 45 - Ct correspond to a higher methylation status, demonstrating hypermethylation in subjects with colorectal cancer.

Figure 30 is a graph depicting Ct values from MSRE-qPCR of LONRF2 '281 for subjects with colorectal cancer and control subjects (healthy subjects, subjects with non-advanced adenoma, and subjects with other cancers). The data represent the fourth group of subjects (774 subjects). For presentation purposes, Ct values are subtracted from 45 (45 - Ct). Values of 45 - Ct correspond to a higher methylation status, demonstrating hypermethylation in subjects with colorectal cancer.

Figure 31 is a graph depicting Ct values from MSRE-qPCR of ZNF492 '069 for subjects with colorectal cancer and control subjects (healthy subjects, subjects with non-advanced adenoma, and subjects with other cancers). The data represent the fourth group of subjects (774 subjects). For presentation purposes, Ct values are subtracted from 45 (45 - Ct). Values of 45 - Ct correspond to a higher methylation status, demonstrating hypermethylation in subjects with colorectal cancer.

Detailed description

Colorectal cancer screening

There is a need for improved methods of detection (e.g. screening) of colorectal cancer, including screening for early-stage colorectal cancer. Despite recommendations for screening individuals, e.g., over 50 years of age, colorectal cancer screening programs are often ineffective or unsatisfactory. Improved colorectal cancer screening improves diagnosis and reduces mortality from colorectal cancer.

DNA methylation (e.g., hypermethylation or hypomethylation) can activate or inactivate genes, including genes that have an impact on cancer development (see, e.g., Figure 20). Thus, for example, hypermethylation can inactivate one or more genes that normally act to suppress cancer, causing or contributing to the development of cancer in a sample or subject.

The present disclosure includes the discovery that determining the methylation status of one or more methylation loci provided herein, and/or the methylation status of one or more DMRs provided herein, and/or the methylation status of one or more methylation sites provided herein, provides colorectal cancer screening, for example, with a high degree of sensitivity and/or specificity. The present disclosure relates to compositions and methods that include or relate to colorectal cancer methylation biomarkers that, individually or in plural panels comprising two or more colorectal cancer methylation biomarkers, provide colorectal cancer screening, for example, with a high degree of specificity and/or sensitivity.

A colorectal cancer methylation biomarker of the present disclosure is selected from a methylation locus that is or includes ALK, LONRF2, ADAMTS2, FGF14, DMRT1, ST6GALNAC5, MCIDAS, PDGFD, GSG1L, ZNF492, ZNF568, ZNF542, ZNF471, ZNF132, JAM2, and CNRIP1 (see, e.g., Table 1). A colorectal cancer DMR is selected from ALK '434, CNRIP1 '232, CNRIP1 '272, LONRF2 '281, LONRF2 '387, ADAMTS2 '254, ADAMTS2 '284, ADAMTS2 '328, FGF14 '577, DMRT1 '934, ST6GALNAC5 '456, MCIDAS '855, MCIDAS '00 3, PDGFD '388, PDGFD '921, GSG1L '861, ZNF492 '499, ZNF492 '069, ZNF568 '252, ZNF568 '405, ZNF542 '525, ZNF542 '502, ZNF471 '527, ZNF471 '558, ZNF471 '662, ZNF132 '268, ZNF132 '415 and JAM2 '320 (see, for example, Table 7).

For the avoidance of doubt, any methylation biomarker referred to herein may be, or be included in, a colorectal cancer methylation biomarker, but is not limited to.

In some embodiments, a colorectal cancer methylation biomarker may be or include a single methylation locus. In some embodiments, a colorectal cancer methylation biomarker may be or include two or more methylation loci. In some embodiments, a colorectal cancer methylation biomarker may be or include a single differentially methylated region (DMR). In some embodiments, a methylation locus may be or include two or more DMRs. In some embodiments, a methylation biomarker may be or include a single methylation site. In other embodiments, a methylation biomarker may be or include two or more methylation sites. In some embodiments, a methylation locus may include two or more DMRs and further include DNA regions adjacent to one or more of the included DMRs.

In some cases, a methylation locus is or includes a gene, such as a gene provided in Table 1. In some cases, a methylation locus is or includes a portion of a gene, for example, a portion of a gene provided in Table 1. In some cases, a methylation locus includes, but is not limited to, identified nucleic acid boundaries of a gene.

In some cases, a methylation locus is or includes a coding region of a gene, such as a coding region of a gene provided in Table 1. In some cases, a methylation locus is or includes a portion of a gene's coding region, for example, a portion of the coding region of a gene provided in Table 1. In some cases, a methylation locus includes, but is not limited to, identified nucleic acid boundaries of a gene's coding region.

In some embodiments, a methylation locus is or includes a promoter and/or other regulatory region of a gene, such as a promoter and/or other regulatory region of a gene provided in Table 1. In some embodiments, a methylation locus is or includes a portion of a promoter and/or regulatory region of a gene, for example, a portion of a promoter and/or regulatory region of a gene provided in Table 1. In some embodiments, a methylation locus includes, but is not limited to, identified nucleic acid boundaries of a promoter and/or other regulatory region of a gene. In some embodiments, a methylation locus is or includes a high CpG density promoter or a portion thereof.

In some embodiments, a methylation locus is or includes a non-coding sequence. In some embodiments, a methylation locus is or includes one or more exons and/or one or more introns. In some embodiments, a methylation locus includes a region of DNA extending a predetermined number of nucleotides upstream of a coding sequence, and/or a region of DNA extending a predetermined number of nucleotides downstream of a coding sequence. In various instances, a predetermined number of nucleotides upstream and/or downstream can be or include, for example, 500 bp, 1 kb, 2 kb, 3 kb, 4 kb, 5 kb, 10 kb, 20 kb, 30 kb, 40 kb, 50 kb, 75 kb, or 100 kb. Those skilled in the art will appreciate that methylation biomarkers that may impact the expression of a coding sequence may typically be within either of these distances from the coding sequence, in the 5' direction and/or in the 3' direction.

Those skilled in the art will appreciate that a methylation locus identified as a methylation biomarker need not necessarily be assayed in a single experiment, reaction, or amplicon. A single methylation locus identified as a colorectal cancer methylation biomarker can be assayed, for example, in a method that includes independently amplifying (or providing oligonucleotide primers and conditions sufficient for amplification) one or more distinct or overlapping DNA regions within a methylation locus, for example, one or more distinct or overlapping DMRs. Those skilled in the art will further appreciate that a methylation locus identified as a methylation biomarker need not be analyzed to determine the methylation status of every nucleotide, or every CpG, present within the methylation locus. Instead, a methylation locus that is a methylation biomarker can be analyzed, for example, by analysis of a single region of DNA within the methylation locus, for example, by analysis of a single DMR within the methylation locus.

The DMRs of the present disclosure may be a methylation locus or include a portion of a methylation locus. In some cases, a DMR is a region of DNA with a methylation locus that is, for example, 1 to 5,000 bp in length. In various embodiments, a DMR is a region of DNA with a methylation locus that is equal to or less than 5,000 bp, 4,000 bp, 3,000 bp, 2,000 bp, 1,000 bp, 950 bp, 900 bp, 850 bp, 800 bp, 750 bp, 700 bp, 650 bp, 600 bp, 550 bp, 500 bp, 450 bp, 400 bp, 350 bp, 300 bp, 250 bp, 200 bp, 150 bp, 100 bp, 50 bp, 40 bp, 30 bp, 20 bp, or 10 bp in length. In some embodiments, a<d>M<r>is 1, 2, 3, 4, 5, 6, 7, 8, or 9 bp in length.

Methylation biomarkers, including, without limitation, methylation loci and DMRs referred to herein, may include at least one methylation site that is a colorectal cancer methylation biomarker.

For clarity, those skilled in the art will appreciate that the term methylation biomarker is used broadly, such that a methylation locus may be a methylation biomarker that includes one or more DMRs, each such DMR is itself also a methylation biomarker, and each such DMR may include one or more methylation sites, each such methylation site is itself also a methylation biomarker. Furthermore, a methylation biomarker may include two or more methylation loci. Accordingly, status as a methylation biomarker is not based on the contiguity of nucleic acids included in a biomarker, but rather on the existence of a change in methylation status for included DNA region(s) between a first state and a second state, such as between colorectal cancer and controls.

As provided herein, a methylation locus may be any one of one or more methylation loci, each such methylation loci is, includes, or is a portion of a gene identified in Table 1. In some particular embodiments, a colorectal cancer methylation biomarker includes a single methylation locus that is, includes, or is a portion of a gene identified in Table 1. For example, in various embodiments, e.g., as described herein, a colorectal cancer methylation biomarker may include a methylation locus that is, includes, or is a portion of a gene selected from ZNF132, ADAMTS2, ZNF542, LONRF2, ZNF492, FGF14, ST6GALNAC5, PDGFD, ZNF471, JAM2, GSG1L, DMRT1, and MCIDAS.

In some particular embodiments, a colorectal cancer methylation biomarker includes two or more methylation loci, each of which is, includes, or is a portion of a gene identified in Table 1. In some embodiments, a colorectal cancer methylation biomarker includes 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, or 16 methylation loci, each of which is, includes, or is a portion of a gene identified in Table 1.

In some particular embodiments, a colorectal cancer methylation biomarker includes two or more methylation loci, each of such two or more methylation loci is, includes, or is a portion of a gene identified in any one of Tables 1 to 6. In some particular embodiments, a colorectal cancer methylation biomarker includes two or more methylation loci, each of such two or more methylation loci is, includes, or is a portion of a gene identified in any one of Tables 2 to 6. In some particular embodiments, a colorectal cancer methylation biomarker includes two or more methylation loci, each of such two or more methylation loci is, includes, or is a portion of a gene identified in Table 1. In some particular embodiments, a colorectal cancer methylation biomarker includes two methylation loci, each of such two or more methylation loci is, includes, or is a portion of a gene identified in Table 2. In some particular embodiments, a colorectal cancer methylation biomarker includes three methylation loci, each of such three methylation loci is, includes, or is a portion of a gene identified in Table 3. In some particular embodiments, a colorectal cancer methylation biomarker includes four methylation loci, each of such four methylation loci is, includes, or is a portion of a gene identified in Table 4. In some particular embodiments, a colorectal cancer methylation biomarker includes six methylation loci, each of such six methylation loci is, includes, or is a portion of a gene identified in Table 5. In some particular embodiments, a colorectal cancer methylation biomarker includes eleven methylation loci, each of such eleven methylation loci is, includes, or is a portion of a gene identified in Table 6. In various particular embodiments, a colorectal cancer methylation biomarker includes four methylation loci, each of such four methylation loci is, includes, or is a portion of a gene identified in Table 4. colorectal cancer or colorectal cancer methylation biomarker panel includes one or more methylation loci of the present disclosure, but does not include a methylation locus that is, includes, or is a portion of one or more of FGF14, ZNF471, PDGFD, and ALK.

Table 1. Methylation loci identified by gene name

Table 2. Combination of 2 methylation loci

Table 3. Combination of 3 methylation loci

Table 4. Combination of 4 methylation loci

_

_

_

_

S

Table 5. Combination of 6 methylation loci

Table 6. Combination of 11 methylation loci

As described herein, a colorectal cancer methylation biomarker may be any one or more DMRs, each of such DMRs being present at a methylation locus that is, includes, or is a portion of a gene identified in Table 1. A colorectal cancer methylation biomarker is or includes a single DMR that is, includes all or a portion of, or is present in a gene identified in Table 1. For example, a colorectal cancer methylation biomarker may include a single DMR that is, includes all or a portion of, or is present in a gene selected from ALK, CNRIP1, LONRF2, ADAMTS2, FGF14, DMRT1, ST6GALNAC5, MCIDAS, PDGFD, GSG1L, ZNF492, ZNF568, ZNF542, ZNF471, ZNF132, and JAM2.

A colorectal cancer methylation biomarker includes two or more DMRs, each of which is, includes all or a portion of, or is present in a gene identified in Table 1. In some embodiments, a colorectal cancer methylation biomarker includes 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, or 16 DMRs, each of which is, includes all or a portion of, or is present in a gene identified in Table 1.

A colorectal cancer methylation biomarker includes two or more DMRs, each of such two or more DMRs is, includes all or a portion of, or is present in a gene identified in any one of Tables 1-6. A colorectal cancer methylation biomarker includes two DMRs, two DMRs including DMRs that are, include all or a portion of, or are present in the genes identified in Table 2. A colorectal cancer methylation biomarker includes three DMRs, three DMRs including DMRs that are, include all or a portion of, or are present in the genes identified in Table 3. A colorectal cancer methylation biomarker includes four DMRs, four DMRs including DMRs that are, include all or a portion of, or are present in the genes identified in Table 4. A colorectal cancer methylation biomarker includes six DMRs, six DMRs including DMRs that are, include all or a portion of, or are present in the genes identified in Table 5. A colorectal cancer methylation biomarker includes eleven DMRs, eleven DMRs including DMRs that are, include all or a portion of, or are present in the genes identified in Table 6. identified in Table 6. A colorectal cancer methylation biomarker or panel of colorectal cancer methylation biomarkers includes one or more DMRs, but the one or more DMRs do not include a DMR that is, includes all or a portion of, or is present in one or more of FGF14, ZNF471, PDGFD, and ALK.

As described herein, a colorectal cancer methylation biomarker may include any one or more DMRs, each of such DMR is, includes all of, or includes a portion of a DMR identified in Table 7, including, without limitation, DMRs specifically as identified in Table 7. A colorectal cancer methylation biomarker is or includes a single DMR that is, includes all of, or includes a portion of a DMR identified in Table 7, including, without limitation, a DMR specifically as identified in Table 7, for example, a DMR from Table 7 selected from the group of DMRs including, without limitation, ALK' 434, CNRIP1' 232, CNRIP1' 272, LONRF2' 281, LONRF2' 387, ADAMTS2' 254, ADAMTS2' 284, ADAMTS2' 328, FGF14' 577, DMRT1 '934, ST6GALNAC5 '456, MCIDAS '855, MCIDAS '003, PDGFD '388, PDGFD '921, GSG1L '861, ZNF492 '499, ZNF492 '069, ZNF568 '252, ZNF568 '405, ZNF542 '525, ZNF542 '502, 71 '527, ZNF471 '558, ZNF471 '662, ZNF132 '268, ZNF132 '415 and JAM2 '320. For example, a colorectal cancer methylation biomarker may include a single DMR that is, includes all of, or includes a portion of a DMR selected from LONRF2'281, LONRF2'387, ADAMTS2'254, ADAMTS2'284, ADAMTS2'328, FGF14'577, ST6GALNAC5'456, PDGFD'388, PDGFD'921, ZNF492'499, ZNF492'069, ZNF542'525, ZNF542'502, ZNF471'527, ZNF471'558, and ZNF471'662.

A colorectal cancer methylation biomarker includes two or more DMRs, each of such DMRs is, includes all of, or includes a portion of a DMR identified in Table 7, including, without limitation, DMRs specifically as identified in Table 7. A colorectal cancer methylation biomarker includes 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, or 28 DMRs, each of such DMRs is, includes all of, or includes a portion of a DMR identified in Table 7, including, without limitation, DMRs specifically as identified in Table 7.

A colorectal cancer methylation biomarker includes two or more DMRs, each of such two or more DMRs is, includes all of, or includes a portion of a DMR identified in any one of Tables 7 to 12, including, without limitation, DMRs and combinations thereof specifically as identified in Tables 8 to 12. A colorectal cancer methylation biomarker includes two DMRs, two DMRs being the DMRs identified in Table 8. In some particular embodiments, a colorectal cancer methylation biomarker includes three DMRs, three DMRs being the DMRs identified in Table 9. A colorectal cancer methylation biomarker includes five DMRs, five DMRs being the DMRs identified in Table 10. A colorectal cancer methylation biomarker includes eight DMRs, eight DMRs being the DMRs identified in Table 11. A colorectal cancer methylation biomarker includes fifteen DMRs, fifteen DMRs that are the DMRs identified in Table 12. A colorectal cancer methylation biomarker or panel of colorectal cancer methylation biomarkers includes one or more DMRs from Table 7, but the one or more DMRs do not include one or more, or all, of the DMRs of FGF14, ZNF471, PDGFD, and ALK, for example, do not include one or more, or all, of the DMRs of FGF14, ZNF471, PDGFD, and ALK as given in Table 7.

Table 7. DMR of colorectal cancer

Table 8. Combination of 2 DMRs

Table 9. Combination of 3 DMRs

Table 10. Combination of 5 DMRs

Table 11. Combination of 8 DMRs

gene name___________ | chr | start site__________ | termination site

Table 12. Combination of 15 DMRs

In various embodiments, a methylation biomarker can be or include one or more individual nucleotides (e.g., a single individual cytosine residue in the context of CpGs) or a plurality of individual cytosine residues (e.g., from a plurality of CpGs) present within one or more methylation loci (e.g., one or more DMRs) provided herein. Thus, in certain embodiments a methylation biomarker is or includes methylation status of a plurality of individual methylation sites.

In various embodiments, a methylation biomarker is, includes, or is characterized by a change in methylation status that is a change in the methylation of one or more methylation sites within one or more methylation loci (e.g., one or more DMRs). In various embodiments, a methylation biomarker is or includes a change in methylation status that is a change in the number of methylated sites within one or more methylation loci (e.g., one or more DMRs). In various embodiments, a methylation biomarker is or includes a change in methylation status that is a change in the frequency of methylation sites within one or more methylation loci (e.g., one or more DMRs). In various embodiments, a methylation biomarker is or includes a change in methylation status that is a change in the pattern of methylation sites within one or more methylation loci (e.g., one or more DMRs).

In various embodiments, the methylation status of one or more methylation loci (e.g., one or more DMRs) is expressed as a fraction or percentage of the one or more methylation loci (e.g., the one or more DMRs) present in a sample that are methylated, for example, as a fraction of the number of individual DNA strands in a sample that are methylated at one or more particular methylation loci (e.g., one or more particular DMRs). Those skilled in the art will appreciate that, in some cases, the methylation fraction or percentage can be calculated from the ratio of methylated DMRs to unmethylated DMRs for one or more DMRs analyzed, for example, within a sample.

In various embodiments, the methylation status of one or more methylation loci (e.g., one or more DMRs) is compared to a reference methylation status value and/or to a methylation status of the one or more methylation loci (e.g., one or more DMRs) in a reference sample. In some cases, a reference is a non-concurrent sample from the same source, e.g., a previous sample from the same source, e.g., from the same subject. In some cases, a reference for the methylation status of one or more methylation loci (e.g., one or more DMRs) is the methylation status of the one or more methylation loci (e.g., one or more DMRs) in a sample (e.g., a sample from a subject), or a plurality of samples, that are known to represent a particular state (e.g., a cancerous state or a non-cancerous state). Thus, a reference may be or include one or more predetermined thresholds, which thresholds may be quantitative (e.g., a methylation value) or qualitative. In some cases, a reference for the methylation status of a DMR is the methylation status of a nucleotide or a plurality of nucleotides (e.g., a plurality of contiguous oligonucleotides) present in the same sample that does not include nucleotides from the DMR. Those skilled in the art will appreciate that a reference average is typically produced by measurement using methodology identical, similar, or comparable to that by which the non-reference measurement was made.

Without wishing to be bound by any particular scientific theory, Figure 20 provides a schematic of one possible mechanism by which hypermethylation or hypomethylation of a gene regulatory sequence can impact expression. As shown in Figure 20, hypomethylation can result in increased expression and/or hypermethylation can result in suppression of expression. In various embodiments, increased methylation of expression regulatory regions, such as promoter regions and enhancer regions, compared to a reference, can reduce or silence expression of an operably linked gene, for example, of an operably linked gene that normally acts to suppress cancer. In various embodiments, reduced methylation of expression regulatory regions, such as promoter regions and enhancer regions, compared to a reference, can increase expression of an operably linked gene, for example, of an operably linked gene that has an activity that contributes to oncogenesis. Without wishing to be bound by any particular scientific theory, DNA methylation may provide a more chemically and biologically stable indicator of cancer status than RNA expression or protein expression per se.

Methylation is generally considered to be highly tissue-specific, providing a dimension of information not necessarily present in DNA sequence analysis.

Methylation events that contribute substantially to oncogenesis may occur, for example, in DNA regions regulating expression (e.g., in a promoter region, enhancer region, transcription factor binding site, CTCF binding site, CpG island, or other sequence) operably linked to cancer-associated genes such as genes that normally act to suppress cancer. Thus, inactivation of genes that normally act to suppress cancer results in, or contributes to, oncogenesis. In addition, hypermethylation is commonly found at CpG islands.

Cancers

The methods and compositions of the present disclosure are useful for screening for cancer, particularly colorectal cancer. Colorectal cancers include, but are not limited to, colon cancer, rectal cancer, and combinations thereof. Colorectal cancers include metastatic colorectal cancers and non-metastatic colorectal cancers. Colorectal cancers include cancer located in the proximal part of the colon and cancer located in the distal part of the colon.

Colorectal cancers include colorectal cancers in any of the various possible stages known in the art, including, for example, stage I, stage II, stage III, and stage IV colorectal cancers (e.g., stages 0, I, IIA, IIB, IIC, IIIA, IIIB, IIIC, IVA, IVB, and IVC). Colorectal cancers include all stages of the tumor/node/metastasis (TNM) staging system. With respect to colorectal cancer, T may refer to whether the tumor has grown into the wall of the colon or rectum, and, if so, into how many layers; N may refer to whether the tumor has spread to lymph nodes, and, if so, how many lymph nodes and where they are located; and M may refer to whether the cancer has spread to other parts of the body, and, if so, which parts and to what extent. Particular stages of T, N, and M are known in the art. T stages may include TX, t 0, Tis, T1, T2, T3, T4a, and T4b; N stages may include NX, N0, N1a, N1b, N1c, N2a, and N2b; M stages may include M0, M1a, and M1b. In addition, grades of colorectal cancer may include GX, G1, G2, G3, and G4. Various means of staging cancer, and colorectal cancer in particular, are well known in the art and are summarized, for example, on the web at cancer.net/cancer-types/colorectal-cancer/stages.

In some cases, the present disclosure includes screening for early stage colorectal cancer. Early stage colorectal cancers may include, for example, colorectal cancers that are localized within a subject, for example, as they have not yet spread to lymph nodes in the subject, for example, lymph nodes near the cancer (stage N0), and have not spread to distant sites (stage M0). Early stage cancers include colorectal cancers corresponding to, for example, stages 0 through II C.

Thus, colorectal cancers of the present disclosure include, but are not limited to, premalignant colorectal cancer and malignant colorectal cancer. The methods and compositions of the present disclosure are useful for screening for colorectal cancer in all its forms and stages.

Subjects and samples

A sample analyzed using methods and compositions provided herein may be any biological sample and/or any sample that includes nucleic acid. In various particular embodiments, a sample analyzed using methods and compositions provided herein may be a sample from a mammal. In various particular embodiments, a sample analyzed using methods and compositions provided herein may be a sample from a human subject. In various particular embodiments, a sample analyzed using methods and compositions provided herein may be a sample from a mouse, rat, pig, horse, chicken, or cow.

In various instances, a human subject is a subject diagnosed or seeking diagnosis as having, diagnosed or seeking diagnosis as being at risk for, and/or diagnosed or seeking diagnosis as being at immediate risk for, a cancer such as colorectal cancer. In various instances, a human subject is a subject identified as being in need of colorectal cancer screening. In some instances, a human subject is a subject identified as being in need of colorectal cancer screening by a medical professional. In various instances, a human subject is identified as being in need of colorectal cancer screening due to age, for example, due to age equal to or greater than 50 years of age, for example, age equal to or greater than 50, 55, 60, 65, 70, 75, 80, 85, or 90 years of age. In various cases, a human subject is a subject who has not been diagnosed as having, is at risk for, is at immediate risk of, or is not diagnosed as having and/or seeking diagnosis for a cancer such as colorectal cancer, or any combination thereof.

A sample from a subject, e.g., a human or other mammalian subject, can be a sample, e.g., of blood, blood component, cfDNA, ctDNA, stool, or colorectal tissue. In some particular embodiments, a sample is an excretion or bodily fluid from a subject (e.g., stool, blood, lymph, or urine from a subject) or a colorectal cancer tissue sample. A sample from a subject can be a cellular or tissue sample, e.g., a cellular or tissue sample that is from a cancer or includes cancer cells, e.g., from a tumor or metastatic tissue. In various embodiments, a sample from a subject, e.g., a human or other mammalian subject, can be obtained by biopsy (e.g., fine needle aspiration or tissue biopsy) or surgery.

In various particular embodiments, a sample is a cell-free DNA (cfDNA) sample. cfDNA is typically found in human body fluids (e.g., plasma, serum, or urine) in short double-stranded fragments. The concentration of cfDNA is typically low, but may increase significantly under particular conditions, including, but not limited to, pregnancy, autoimmune disorder, myocardial infarction, and cancer. Circulating tumor DNA (cfDNA) is the circulating DNA component derived specifically from cancer cells. cfDNA may be present in human body fluids bound to leukocytes and erythrocytes or not bound to leukocytes and erythrocytes. Various tests for the detection of tumor-derived cfDNA are based on the detection of genetic or epigenetic modifications that are characteristic of cancer (e.g., of a relevant cancer). Genetic or epigenetic modifications characteristic of cancer may include, but are not limited to, oncogenic or cancer-associated mutations in tumor suppressor genes, activated oncogenes, hypermethylation, and/or chromosomal disorders. Detection of genetic or epigenetic modifications characteristic of cancer may confirm that the detected cfDNA is ctDNA.

LCDNA and ctDNA provide a real-time or near real-time metric of the methylation status of a tissue of origin. LCDNA and ctDNA demonstrate a half-life in blood of approximately 2 hours, such that a sample taken at a given time provides a relatively timely reflection of the status of a tissue of origin. Various methods of isolating nucleic acids from a sample (e.g., isolating LCDNA from blood or plasma) are known in the art. Nucleic acids may be isolated, for example, without limitation, by conventional DNA purification techniques, by direct gene capture (e.g., by clarifying a sample to remove assay inhibiting agents and capturing a target nucleic acid, if present, from the clarified sample with a capture agent to produce a capture complex, and isolating the capture complex to recover the target nucleic acid).

Methods for measuring methylation status

Methylation status may be measured by a variety of methods known in the art and/or by methods provided herein. Those skilled in the art will appreciate that a method for measuring methylation status may be generally applied to samples from any source and of any kind, and will further be aware of processing steps available to modify a sample into a form suitable for measurement by a given methodology. Methods of measuring methylation status include, without limitation, methods including methylation-state-specific polymerase chain reaction (PCR), methods including nucleic acid sequencing, methods including mass spectrometry, methods including methylation-specific nucleases, methods including mass-based separation, methods including target-specific capture, and methods including methylation-specific oligonucleotide primers. Particular assays for methylation use a bisulfite reagent (e.g., hydrogen sulfite ions). Bisulfite reagents may include, but are not limited to, bisulfite, disulfite, hydrogen sulfite, or combinations thereof, reagents that may be useful in distinguishing methylated from unmethylated nucleic acids. Bisulfite interacts differently with cytosine and 5-methylcytosine. In typical bisulfite-based methods, contact of DNA with bisulfite deaminates unmethylated cytosine to uracil, while methylated cytosine is unaffected; methylated cytosines are selectively retained, but unmethylated cytosines are not. Thus, in a bisulfite-processed sample, uracil residues take the place of, and thus provide an identification signal for, unmethylated cytosine residues, while the remaining (methylated) cytosine residues thus provide an identification signal for methylated cytosine residues. Bisulfite-processed samples can be analyzed, for example, by PCR. Various methylation assay procedures can be used in conjunction with bisulfite treatment to determine the methylation status of a target sequence such as a<d>M<r>. Such assays can include, but are not limited to, qPCR with methylation-specific restriction enzymes, bisulfite-treated nucleic acid sequencing, PCR (e.g., with sequence-specific amplification), PCR with methylation-specific nuclease-assisted minor allele enrichment, and methylation-sensitive high-resolution melting. In some embodiments, DMRs are amplified from a bisulfite-treated DNA sample and a DNA sequencing library is prepared for sequencing according to, for example, an Illumina protocol or Nextera XT shuffle protocol. In certain embodiments, high-throughput and/or next-generation sequencing techniques are used to achieve base pair level resolution of the DNA sequence, allowing for analysis of methylation status.

In various embodiments, methylation status is detected by a method that includes PCR amplification with methylation-specific oligonucleotide primers (MSP methods), e.g., as applied to a bisulfite-treated sample (see, e.g., Herman 1992 Proc. Natl. Acad. Sci. USA 93:9821-9826). The use of methylation state-specific oligonucleotide primers for amplification of bisulfite-treated DNA allows for differentiation between methylated and unmethylated nucleic acids. Oligonucleotide primer pairs for use in MSP methods include at least one oligonucleotide primer capable of hybridizing to the sequence that includes a methylation site, e.g., a CpG. An oligonucleotide primer that includes a T residue at a position complementary to a cytosine residue will selectively hybridize to templates in which the cytosine was unmethylated prior to bisulfite treatment, whereas an oligonucleotide primer that includes a G residue at a position complementary to a cytosine residue will selectively hybridize to templates in which the cytosine was methylated prior to bisulfite treatment. MSP results can be obtained with or without amplicon sequencing, for example using gel electrophoresis. MSP (methylation-specific PCR) allows highly sensitive detection (0.1% detection level of alleles, with full specificity) of locus-specific DNA methylation using PCR amplification of bisulfite-converted DNA.

Another method that can be used to determine the methylation status after bisulfite treatment of a sample is methylation-sensitive high-resolution melting (MS-HRM) (see e.g. Hussmann 2018 Methods Mol Biol. 1708:551–571). MS-HRM is a tube-based, PCR-based method to detect methylation levels at specific loci of interest based on hybridization melting. Bisulfite treatment of DNA prior to performing MS-HRM ensures a different base composition between methylated and unmethylated DNA, which is used to separate the resulting amplicons by high-resolution melting. A unique primer design facilitates high sensitivity of the assays allowing the detection of up to 0.1–1% of methylated alleles in an unmethylated background. Oligonucleotide primers for MS-HRM assays are designed to be complementary to the methylated allele, and a specific annealing temperature allows these primers to hybridize to both methylated and unmethylated alleles thereby increasing the sensitivity of the assays.

Another method that can be used to determine the methylation status after bisulfite treatment of a sample is quantitative multiplex methylation-specific pCR (QM-MSP). QM-MSP uses methylation-specific primers for sensitive quantification of DNA methylation (see e.g. Fackler 2018 Methods Mol Biol. 1708:473–496). QM-MSP is a two-step PCR approach, where in the first step a gene-specific primer pair (forward and reverse) amplifies methylated and unmethylated copies of the same gene simultaneously and in multiplex, in one PCR reaction. This methylation-independent amplification step yields amplicons of up to 109 copies per pl after 36 PCR cycles. In the second step, amplicons from the first reaction are quantified with a standard curve using real-time PCR and two independent fluorophores to detect methylated/unmethylated DNA of each gene in the same well (e.g., 6FAM and VIC). One methylated copy can be detected in 100,000 copies of the reference gene.

Another method that can be used to determine the methylation status after bisulfite treatment of a sample is methylation-specific nuclease-assisted minor allele enrichment (MS-NaME) (see, e.g., Liu 2017 Nucleic Acids Res. 45(6):e39). Ms-NaME is based on the selective hybridization of probes to target sequences in the presence of double-stranded (ds) DNA-specific DNA nuclease (DSN), such that hybridization results in regions of double-stranded DNA that are subsequently digested by DSN. Thus, oligonucleotide probes that target unmethylated sequences generate local double-stranded regions resulting in digestion of unmethylated targets; oligonucleotide probes that can hybridize to methylated sequences generate local double-stranded regions resulting in digestion of methylated targets, leaving methylated targets intact. Furthermore, oligonucleotide probes can direct DSN activity to multiple targets on bisulfite-treated DNA simultaneously. Subsequent amplification can enrich for undigested sequences. Ms-NaME can be used either independently or in combination with other techniques provided herein.

Another method that can be used to determine the methylation status after bisulfite treatment of a sample is methylation-sensitive single nucleotide primer extension (Ms-SNuPE™) (see, e.g., Gonzalgo 2007 Nat Protoc. 2(8):1931-6). In Ms-SNuPE, strand-specific PCR is performed to generate a DNA template for quantitative methylation analysis using Ms-SNuPE. SNuPE is then performed with oligonucleotide(s) designed to hybridize immediately upstream of the CpG site(s) being interrogated. The reaction products can be electrophoresed on polyacrylamide gels for visualization and quantitation by phosphorimaging analysis. Amplicons may also carry directly or indirectly detectable labels such as a fluorescent tag, radionuclide, or a cleavable molecule fragment or other entity having a mass that can be distinguished by mass spectrometry. Detection may be carried out and/or visualized by, for example, matrix-assisted laser desorption/ionization (MALDI) mass spectrometry or by using electrospray mass spectrometry (ESI).

Some methods that can be used to determine the methylation status after bisulfite treatment of a sample use a first oligonucleotide primer, a second oligonucleotide primer, and an oligonucleotide probe in an amplification-based method. For example, the oligonucleotide primers and probe can be used in a real-time polymerase chain reaction (PCR) or droplet digital PCR (ddPCR) method. In various cases, the first oligonucleotide primer, the second oligonucleotide primer, and/or the oligonucleotide probe selectively hybridize to methylated DNA and/or unmethylated DNA such that the amplification signal or probe indicates the methylation status of a sample.

Other bisulfite-based methods for detecting methylation status (e.g., the presence of 5-methylcytosine level) are reported, for example, in Frommer (1992 Proc Natl Acad Sci USA. 1; 89(5):1827-31).

Some methods that can be used to determine methylation status do not involve bisulfite treatment of a sample. For example, changes in methylation status can be detected by a PCR-based procedure in which DNA is digested with one or more methylation-sensitive restriction enzymes (MSREs) prior to PCR amplification (e.g., by MSRE-qPCR). Typically, MSREs have recognition sites that include at least one CpG motif, such that MSRE activity is blocked from cleaving a potential recognition site if the site includes 5-methylcytosine (see, e.g., Beikircher 2018 Methods Mol Biol. 1708:407–424). Thus, MSREs selectively digest nucleic acids based on the methylation status of the MSRE recognition site; They may digest DNA at MSRE recognition sites that are unmethylated, but not digest DNA at MSRE recognition sites that are methylated. In certain embodiments, an aliquot of sample may be digested with MSREs, generating a processed sample in which unmethylated DNA has been cleaved by the MSREs, such that the proportion of uncleaved and/or amplifiable DNA with at least one methylated site within MSRE recognition sites (e.g., at least one methylated site within each MSRE recognition site of the DNA molecule) is increased relative to uncleaved and/or amplifiable DNA that did not include at least one methylated site within MSRE recognition sites (e.g., did not include at least one methylated site within each MSRE recognition site of the DNA molecule). Uncleaved sequences from a restriction enzyme-digested sample can then be pre-amplified, e.g., in PCR, and quantified, e.g., by qPCR, real-time PCR, or digital PCR. Oligonucleotide primers for MSRE-qPCR amplify regions that include one or more MSRE cleavage sites, and/or a plurality of MSRE cleavage sites. Typically, amplicons that include a plurality of MSRE cleavage sites are more likely to provide robust results. The number of cleavage sites within a DMR amplicon, and in some cases the resulting robustness of determining methylation status for the DMR, can be increased by designing DMRs that include a plurality of MSRE recognition sites (as opposed to a single recognition site) in a DMR amplicon. In various cases, a plurality of MSREs can be applied to the same sample, including, for example, two or more of Acyl, Hin6I, HpyCH4IV, and Hpall (e.g., including Acyl, Hin6I, and HpyCH4IV). A plurality of MSREs (e.g., the combination of Acyl, Hin6I, HpyCH4IV, and Hpall, or the combination of Acyl, Hin6I, and HpyCH4IV) can provide an enhanced frequency of MSRE recognition sites within DMR amplicons.

MSRE-qPCR may also include a pre-amplification step after sample digestion by MSRE but before qPCR in order to improve the amount of sample available, given the low prevalence of lncDNA in blood.

In certain embodiments of MSRE-qPCR, the amount of total DNA is measured in a sample aliquot in native (e.g., undigested) form using, for example, real-time PCR or digital PCR.

Various amplification technologies may be used alone or in conjunction with other techniques described herein for the detection of methylation status. Those skilled in the art, having reviewed the present specification, will understand how to combine various amplification technologies known in the art and/or described herein in conjunction with various other technologies for the determination of methylation status known in the art and/or provided herein. Amplification technologies include, but are not limited to, PCR, e.g., quantitative PCR (qPCR), real-time PCR, and/or digital PCR. Those skilled in the art will appreciate that polymerase amplification can multiplex the amplification of multiple targets in a single reaction. PCR amplicons are typically 100 to 2000 base pairs in length. In various instances, one amplification technology is sufficient to determine methylation status. Digital PCR (dPCR)-based methods involve dividing and distributing a sample across wells of a 96-, 384-, or more-well plate, or into individual emulsion droplets (ddPCR) for example, using a microfluidic device, such that some wells include one or more copies of template and others include no copies of template. Thus, the average number of template molecules per well is less than one prior to amplification. The number of wells in which template amplification occurs provides a measure of the template concentration. If the sample has been in contact with MSRE, the number of wells in which template amplification occurs provides a measure of the concentration of methylated template.

In various embodiments, a fluorescence-based real-time PCR assay, such as MethyLight™, can be used to measure methylation status (see, e.g., Campan 2018 Methods Mol Biol. 1708:497-513). MethyLight is a quantitative, fluorescence-based, real-time PCR method for sensitively detecting and quantifying DNA methylation of candidate regions of the genome. MethyLight is uniquely suited for detecting low frequency methylated DNA regions against a high background of unmethylated DNA as it combines methylation-specific priming with methylation-specific fluorescent probe analysis. Additionally, MethyLight can be combined with digital PCR for highly sensitive detection of individual methylated molecules for use in disease detection and screening.

Real-time PCR-based methods for use in determining methylation status typically include a step of generating a standard curve for unmethylated DNA based on analysis of external standards. A standard curve may be constructed from at least two points and may allow comparison of a real-time Ct value for digested DNA and/or a real-time Ct value for undigested DNA to known quantitative standards. In particular cases, sample Ct values for MSRE-digested and/or undigested samples or sample aliquots may be determined, and genomic DNA equivalents calculated from the standard curve. Ct values of MSRE-digested and undigested DNA may be assessed to identify digested amplicons (e.g., efficiently digested; e.g., giving a Ct value of 45). Unamplified amplicons under either digested or undigested conditions may also be identified. Corrected Ct values for amplicons of interest can then be directly compared across conditions to establish relative differences in methylation status between conditions. Alternatively or additionally, the delta difference between digested and undigested DNA Ct values can be used to establish relative differences in methylation status between conditions.

Methods of measuring methylation status may include, but are not limited to, massively parallel sequencing (e.g., next-generation sequencing) to determine methylation status, e.g., sequencing by synthesis, real-time sequencing (e.g., of single molecules), bead emulsion sequencing, nanopore sequencing, or other sequencing techniques known in the art. In some embodiments, a method of measuring methylation status may include whole genome sequencing, e.g., at base pair resolution.

In certain particular embodiments, MSRE-qPCR, among other techniques, can be used to determine the methylation status of a colorectal cancer methylation biomarker that is or includes a single methylation locus. In certain particular embodiments, MSRE-qPCR, among other techniques, can be used to determine the methylation status of a colorectal cancer methylation biomarker that is or includes two or more methylation loci. In certain particular embodiments, MSRE-qPCR, among other techniques, can be used to determine the methylation status of a colorectal cancer methylation biomarker that is or includes a single differentially methylated region (DMR). In certain particular embodiments, MSRE-qPCR, among other techniques, can be used to determine the methylation status of a colorectal cancer methylation biomarker that is or includes two or more DMRs. In certain particular embodiments, MSRE-qPCR, among other techniques, can be used to determine the methylation status of a colorectal cancer methylation biomarker that is or includes a single methylation site. In certain particular embodiments, MSRE-qPCR, among other techniques, can be used to determine the methylation status of a colorectal cancer methylation biomarker that is or includes two or more methylation sites. A colorectal cancer methylation biomarker can be any colorectal cancer methylation biomarker provided herein. The present disclosure includes, among other things, oligonucleotide primer pairs for amplification of DMRs, for example, for amplification of DMRs identified in Table 7.

In certain particular embodiments, an cfDNA sample is derived from subject plasma and contacted with SERMs that are or include one or more of Acyl, Hin6I, HpyCH4IV, and Hpall (e.g., Acyl, Hin6I, and HpyCH4IV). The digested sample can be pre-amplified with oligonucleotide primer pairs from one or more DMRs, for example, with one or more oligonucleotide primer pairs provided in Table 13. The digested DNA, e.g., pre-amplified digested DNA, can be quantified with qPCR with oligonucleotide primer pairs from one or more DMRs, for example, with one or more oligonucleotide primer pairs provided in Table 13. qPCR ct values can then be determined and used to determine the methylation status of each DMR amplicon.

Those skilled in the art will appreciate that oligonucleotide primer pairs provided in Table 13 may be used according to any combination of colorectal cancer methylation biomarkers identified herein. Those skilled in the art will appreciate that the oligonucleotide primer pairs in Table 13 may be included individually or not included in a given analysis in order to analyze a particular desired combination of DMRs.

The skilled artisan will further appreciate that, although other oligonucleotide primer pairs may be used, the selection and pairing of oligonucleotide primers to produce useful DMR amplicons is non-trivial and represents a substantial contribution.

Those skilled in the art will further appreciate that methods, reagents, and protocols for qPCR are well known in the art. Unlike traditional PCR, qPCR can detect amplicon production over time in the amplification (e.g., at the end of each amplification cycle), often by using an amplification-sensitive fluorescence system, for example, in combination with a thermal cycler with fluorescence detection capability. Two common types of fluorescent reporters used in qPCR include (i) double-stranded DNA-binding dyes that fluoresce substantially more brightly when bound than when unbound; and (ii) labeled oligonucleotides (e.g., labeled oligonucleotide primers or labeled oligonucleotide probes).

Those skilled in the art will appreciate that, in embodiments where a plurality of methylation loci (e.g., a plurality of DMRs) are analyzed for methylation status in a colorectal cancer screening method provided herein, the methylation status of each methylation locus may be measured or represented in any of a variety of ways, and the methylation states of a plurality of methylation loci (preferably each measured and/or represented in the same, similar, or comparable manner) may be analyzed or represented together or cumulatively in any of a variety of ways. In various embodiments, the methylation status of each methylation locus may be measured as a ct value. In various embodiments, the methylation status of each methylation locus may be represented as the difference in ct value between a measured sample and a reference. In various embodiments, the methylation status of each methylation locus may be represented as a qualitative comparison to a reference, for example, by identifying each methylation locus as hypermethylated or non-hypermethylated.

When analyzing a single methylation locus, hypermethylation at the single methylation locus is diagnostic that a subject has or is likely to have colorectal cancer, whereas absence of hypermethylation at the single methylation locus is diagnostic that the subject is likely not to have colorectal cancer.

As disclosed herein, hypermethylation at a single methylation locus (e.g., a single DMR) of a plurality of methylation loci analyzed is diagnostic that a subject has or is likely to have colorectal cancer, while the absence of hypermethylation at any methylation locus of a plurality of methylation loci analyzed is diagnostic that a subject is likely not to have colorectal cancer. Hypermethylation of a certain percentage (e.g., a predetermined percentage) of methylation loci (e.g., at least 10% (e.g., at least 10%, at least 20%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, or 100%)) of a plurality of methylation loci analyzed constitutes a diagnosis that a subject has or may have colorectal cancer, while the absence of hypermethylation of a certain percentage (e.g., a predetermined percentage) of methylation loci (e.g., at least 10% (e.g., at least 10%, at least 20%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, or 100%)) of a plurality of methylation loci analyzed constitutes a diagnosis that a subject has or may have colorectal cancer. 70%, at least 80%, at least 90%, or 100%) of a plurality of methylation loci analyzed constitutes a diagnosis that a subject is not likely to have colorectal cancer. Hypermethylation of a certain number (e.g., a predetermined number) of methylation loci (e.g., at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, or 28 DMRs) of a plurality of methylation loci analyzed (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27 or 28 DMRs) constitutes a diagnosis that a subject has or may have colorectal cancer, whereas the absence of hypermethylation of a certain number (e.g., a predetermined number) of methylation loci (e.g., at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, or 28 DMRs) of a plurality of methylation loci analyzed (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21,22, 23, 24, 25, 26, 27, or 28 DMR) constitutes a diagnosis that a subject is not likely to have colorectal cancer.

In some embodiments, the methylation status of a plurality of methylation loci (e.g., a plurality of DMRs) is measured qualitatively or quantitatively and the measurement for each of the plurality of methylation loci is combined to provide a diagnosis. In some embodiments, the qualitatively or quantitatively measured methylation status of each of a plurality of methylation loci is individually weighted, and the weighted values are combined to provide a single value that can be compared to a reference to provide a diagnosis. To provide just one example of such an approach, a support vector machine (SVM) algorithm can be used to analyze the methylation states of a plurality of methylation loci of the present disclosure to produce a diagnosis. At least one goal of the support vector machine algorithm is to identify a hyperplane in an N-dimensional space (N - the number of features) that differentially classifies the data points with the goal of finding a plane that has the maximum margin, i.e. the maximum distance between data points of both classes. As discussed in the present examples, an SVM model is built with marker values (e.g., ct values) derived from a set of training samples (e.g., the first subject group and/or the second subject group) that are transformed into support vector values based on which a prediction is made. In applying the SVM model to new samples, the samples will be mapped into the vector space of the model and classified as having a probability of belonging to either the first condition or the second condition, for example, based on the location of each new sample relative to the gap between the two conditions. Those skilled in the art will appreciate that once relevant compositions and methods have been identified, vector values can be used in conjunction with an SVM algorithm defined using the R package's predict() function (see Hypertext Transfer Protocol Secure (HTTPS)://cran.rproject.org/web/packages/e1071/index.html) to readily generate a prediction on a new sample. Accordingly, by providing compositions and methods for diagnosing colorectal cancer disclosed herein (and only then), generating a predictive model using algorithm input information in combination with the R package's predict() function (see Hypertext Transfer Protocol Secure (HTTPS)://cran.r-project.org/web/packages/e1071/index.html) to provide a diagnosis of colorectal cancer will be straightforward. By way of example, a non-limiting example of SVM vectors for use in diagnosing colorectal cancer by analyzing the methylation status of a plurality of DMRs provided herein is provided in Table 17. Those skilled in the art will appreciate that, having the present disclosure, the generation of SVM vectors can be achieved according to methods provided herein and otherwise known in the art.

Table 13. Colorectal cancer DMR oligonucleotide primer pairs, e.g. for MSRE-qPCR

Applications

Methods and compositions of the present disclosure can be used in any of a variety of applications. For example, methods and compositions of the present disclosure can be used to screen for, or assist in screening for, colorectal cancer. In various instances, screening using methods and compositions of the present disclosure can detect any stage of colorectal cancer, including, without limitation, early stage colorectal cancer. In some embodiments, colorectal cancer screening using methods and compositions of the present disclosure is applied to individuals 50 years of age or older, e.g., 50, 55, 60, 65, 70, 75, 80, 85, or 90 years of age or older. In some embodiments, colorectal cancer screening using methods and compositions of the present disclosure is applicable to individuals 20 years of age or older, e.g., 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, or 90 years of age or older. In some embodiments, colorectal cancer screening using methods and compositions of the present disclosure is applicable to individuals 20 to 50 years of age, e.g., 20 to 30 years of age, 20 to 40 years of age, 20 to 50 years of age, 30 to 40 years of age, 30 to 50 years of age, or 40 to 50 years of age. In various embodiments, colorectal cancer screening using methods and compositions of the present disclosure is applied to individuals who are experiencing abdominal pain or discomfort, for example, who are experiencing undiagnosed or incompletely diagnosed abdominal pain or discomfort. In various embodiments, colorectal cancer screening using methods and compositions of the present disclosure is applied to individuals who are not experiencing any symptoms that are likely to be associated with colorectal cancer. Thus, in certain embodiments, colorectal cancer screening using methods and compositions of the present disclosure is completely or partially preventative or prophylactic, at least with respect to early or non-early stages of colorectal cancer.

In various embodiments, colorectal cancer screening using methods and compositions of the present disclosure may be applied to an asymptomatic human subject. As used herein, a subject may be referred to as “asymptomatic” if the subject does not report and/or demonstrate by noninvasively observable indicia (e.g., without one, several, or all of a device-based scan, tissue sample analysis, body fluid analysis, surgery, or colorectal cancer screening), sufficient characteristics of colorectal cancer to support a medically reasonable suspicion that the subject is likely to have colorectal cancer and/or cancer. Detection of early-stage colorectal cancer is particularly likely in asymptomatic individuals screened according to methods and compositions of the present disclosure.

In various embodiments, colorectal cancer screening using methods and compositions of the present disclosure may be applied to a symptomatic human subject. As used herein, a subject may be referred to as “symptomatic” if the subject reports and/or demonstrates through noninvasively observable indicia (e.g., without one, several, or all of a device-based scan, tissue sample analysis, body fluid analysis, surgery, or colorectal cancer screening), sufficient features of colorectal cancer to support a medically reasonable suspicion that the subject is likely to have colorectal cancer and/or cancer. Symptoms of colorectal cancer may include, but are not limited to, change in bowel habits (diarrhea, constipation, or narrowing of the stool) that are persistent (e.g., lasting more than 3 days), feeling the urge to have a bowel movement, feeling that is not relieved after a bowel movement, rectal bleeding (e.g., light red blood), blood in the stool (which may cause the stool to appear dark), abdominal cramps, abdominal pain, weakness, fatigue, unintentional weight loss, anemia, and combinations thereof. Those skilled in the art will appreciate that individual symptoms that alone would not indicate or suspect colorectal cancer may do so when present in combination, for example, a combination of abdominal cramps and blood in the stool, to provide just one non-limiting example.

Those skilled in the art will appreciate that regular, preventive and/or prophylactic screening for colorectal cancer improves the diagnosis of colorectal cancer, including and/or particularly early stage cancer. As noted above, early stage cancers include, according to at least one cancer staging system, stages 0 through II C of colorectal cancer. Thus, the present disclosure provides, among other things, methods and compositions particularly useful for the diagnosis and treatment of early stage colorectal cancer. Generally, and particularly in embodiments where colorectal cancer screening according to the present disclosure is performed annually, and/or where a subject is asymptomatic at the time of screening, the methods and compositions of the present invention are especially likely to detect early stage colorectal cancer.

In various embodiments, colorectal cancer screening according to the present disclosure is performed once for a given subject or multiple times for a given subject. In various embodiments, colorectal cancer screening according to the present disclosure is performed on a regular basis, for example, every six months, annually, every two years, every three years, every four years, every five years, or every ten years.

In various embodiments, colorectal cancer screening using methods and compositions disclosed herein will provide a diagnosis of colorectal cancer. In other cases, colorectal cancer screening using methods and compositions disclosed herein will be indicative of a diagnosis of colorectal cancer but not definitive of a diagnosis of colorectal cancer. In various cases where methods and compositions of the present disclosure are used for colorectal cancer screening, screening using methods and compositions of the present disclosure may be followed by an additional diagnostic confirmatory test, which additional test may confirm, support, undermine, or reject a diagnosis resulting from the previous screening, e.g., screening according to the present disclosure. As used herein, a diagnostic confirmatory assay may be a colorectal cancer assay that provides a diagnosis recognized as definitive by medical professionals, for example, a colonoscopy-based diagnosis, or a colorectal cancer assay that substantially increases or decreases the likelihood that a previous diagnosis was correct, for example, a diagnosis resulting from screening according to the present disclosure. Diagnostic confirmatory assays may include existing screening technologies, which generally need improvement with respect to one or more of sensitivity, specificity, and noninvasiveness, particularly in detecting early stage colorectal cancers.

In some embodiments, a diagnostic confirmatory test is a test that is or includes a visual or structural inspection of subject tissues, for example, by colonoscopy. In some embodiments, the colonoscopy includes or is followed by histological analysis. Visual and/or structural tests to detect colorectal cancer may include inspection of the structure of the colon and/or rectum to detect any abnormal tissues and/or structures. The visual and/or structural inspection may be performed, for example, by use of a colonoscope through the rectum or by CT scanning. In some embodiments, a diagnostic confirmatory test is a colonoscopy, for example, that includes or is followed by histological analysis. According to some reports, colonoscopy is currently the predominant and/or most relied upon diagnostic confirmatory test. Another visual and/or structural diagnostic confirmatory test based on computed tomography (CT) is CT colonography, sometimes referred to as virtual colonoscopy. A CT scan uses numerous x-ray images of the colon and/or rectum to produce dimensional representations of the colon. Although useful as a confirmatory diagnostic test, some reports suggest that CT colonography is not a sufficient substitute for colonoscopy, at least in part because a medical professional has not physically accessed the subject's colon to obtain tissue for histologic analysis.

Another confirmatory diagnostic test may be a sigmoidoscopy. In sigmoidoscopy, a sigmoidoscope is used through the rectum to obtain images of portions of the colon and/or rectum. According to some reports, sigmoidoscopy is not widely used.

In some cases, a confirmatory diagnostic assay is a stool-based assay. It is typically recommended that stool-based assays, when used in place of visual or structural inspection, be used at a higher frequency than would be required if visual or structural inspection were used. In some cases, a confirmatory diagnostic assay is a guaiac-based fecal occult blood test or a fecal immunochemical test (gFOBT/FIT) (see, e.g., Navarro 2017 World J Gastroenterol. 23(20):3632-3642). FOBT and FIT are sometimes used for the diagnosis of colorectal cancer (see, e.g., Nakamura 2010 J Diabetes Investig. Oct 19;1(5):208-11). FIT relies on the detection of fecal occult blood, the presence of which is often indicative of colorectal cancer but is often not in sufficient volume to permit visual identification. For example, in a typical FIT, the test uses a hemoglobin-specific reagent to test for occult blood in a stool sample. In many cases, FIT kits are suitable for use by individuals in their own home. When used in the absence of other confirmatory diagnostic tests, FIT may be recommended for use on an annual basis. FIT is generally not relied upon to provide sufficient diagnostic information for a conclusive diagnosis of colorectal cancer.

Diagnostic confirmatory assays also include gFOBT, which is designed to detect fecal occult blood by chemical reaction. Like FIT, when used in the absence of other diagnostic confirmatory assays, gFOBT may be recommended for use on an annual basis. gFOBT is generally not relied upon to provide sufficient diagnostic information for a conclusive diagnosis of colorectal cancer. Diagnostic confirmatory assays may also include stool DNA testing. Stool DNA tests for colorectal cancer may be designed to identify DNA sequences characteristic of cancer in stool samples. When used in the absence of other diagnostic confirmatory assays, stool DNA testing may be recommended for use every three years. Stool DNA testing is generally not relied upon to provide sufficient diagnostic information for a conclusive diagnosis of colorectal cancer.

One particular screening technology is a stool-based screening test (Cologuard® (Exact Sciences Corporation, Madison, WI, USA), which combines a FIT assay with DNA analysis to detect aberrant modifications such as mutation and methylation. The Cologuard® test demonstrates improved sensitivity compared to the FIT assay alone but may be clinically impractical or ineffective due to low compliance rates – low compliance rates that are at least in part due to subject dislike of using stool-based assays (see e.g. doi: 10.1056/NEJMc1405215 (e.g. 2014 N Engl J Med. 371(2):184–188)). The Cologuard® test appears to leave almost half of the eligible population out of screening programs (see e.g. van der Vlugt 2017 Br J Cancer. 116(1 ):44-49). The use of screening as provided herein, for example by a blood-based test, will increase the number of individuals choosing to undergo colorectal cancer screening (see, for example, Adler 2014 BMC Gastroenterol.

14:183; Liles 2017 Cancer Treatment and Research Communications 10: 27-31). To the best of our knowledge, only one existing colorectal cancer screening technology, Epiprocolon, is FDA-approved and CE-IVD marked and is blood-based. Epiprocolon is based on hypermethylation of the SEPT9 gene. The Epiprocolon test has a low accuracy for detection of colorectal cancer with a sensitivity of 68% and an advanced adenoma sensitivity of only 22% (see, e.g., Potter 2014 Clin Chem. 60(9): 1183-91). There is a need in the art, among others, for noninvasive colorectal cancer screening that is likely to achieve high subject adherence with high and/or improved specificity and/or sensitivity.

In various embodiments, screening according to methods and compositions of the present disclosure reduces colorectal cancer mortality, for example, by diagnosing colorectal cancer early. Data support that colorectal cancer screening reduces colorectal cancer mortality, the effect of which persisted for over 30 years (see, e.g., Shaukat 2013 N Engl J Med. 369(12):1106-14). Furthermore, colorectal cancer is particularly difficult to treat, at least in part because colorectal cancer, in the absence of timely screening, may not be detected until the cancer has progressed beyond the early stages. For this reason at least, treatment of colorectal cancer is often unsatisfactory. To maximize improvement of colorectal cancer outcomes across the population, use of screening according to the present disclosure may be coupled, for example, with inclusion of eligible subjects to ensure extended screening.

Colorectal cancer screening including one or more methods and/or compositions disclosed herein is followed by treatment of colorectal cancer, e.g., treatment of early stage colorectal cancer. Treatment of colorectal cancer, e.g., early stage colorectal cancer, includes administration of a therapeutic regimen that includes one or more of surgery, radiation therapy, and chemotherapy. Treatment of colorectal cancer, e.g., early stage colorectal cancer, includes administration of a therapeutic regimen that includes one or more of treatments provided herein for the treatment of stage 0 colorectal cancer, stage I colorectal cancer, and/or stage II colorectal cancer.

Colorectal cancer treatment includes treatment of early-stage colorectal cancer, such as stage 0 colorectal cancer or stage I colorectal cancer, with one or more of surgical removal of cancerous tissue, for example, by local excision (for example, using a colonoscope), partial colectomy, or complete colectomy.

Treatment of colorectal cancer includes treatment of early-stage colorectal cancer, such as stage II colorectal cancer, with one or more of surgical removal of cancer tissue (for example, by local excision (for example, using a colonoscope), partial colectomy, or complete colectomy), surgery to remove lymph nodes near the colorectal cancer tissue that has been identified, and chemotherapy (for example, giving one or more of 5-FU and leucovorin, oxaliplatin, or capecitabine).

Treatment of colorectal cancer includes treatment of stage III colorectal cancer with one or more of surgical removal of cancer tissue (for example, by local excision (for example, by colonoscopy-based excision), partial colectomy, or complete colectomy), surgical removal of lymph nodes near identified colorectal cancer tissue, chemotherapy (for example, giving one or more of 5-FU, leucovorin, oxaliplatin, capecitabine, for example, in a combination of (i) 5-FU and leucovorin, (ii) 5-FU, leucovorin, and oxaliplatin (for example, FOLFOX), or (iii) capecitabine and oxaliplatin (for example, CAPEOX)), and radiation therapy.

Colorectal cancer treatment includes treatment of stage IV colorectal cancer by one or more of surgical removal of cancer tissue (e.g., by local excision (e.g., by colonoscope), partial colectomy, or complete colectomy), surgical removal of lymph nodes near identified colorectal cancer tissue, surgical removal of metastases, chemotherapy (e.g., administration of one or more of 5-FU, leucovorin, oxaliplatin, capecitabine, irinotecan, VEGF-targeted therapeutic (e.g., bevacizumab, ziv-aflibercept, or ramucirumab), EGFR-targeted therapeutic (e.g., cetuximab or panitumumab), regorafenib, trifluridine, and tipiracil, for example, in a combination of or including (i) 5-FU and leucovorin, (ii) 5-FU, leucovorin, and oxaliplatin (e.g., FOLFOX), (iii) (i) capecitabine and oxaliplatin (e.g., CAPEOX), (iv) leucovorin, 5-FU, oxaliplatin, and irinotecan (FOLFOXIRI), and (v) trifluridine and tipiracil (Lonsurf), radiation therapy, hepatic arterial infusion (e.g., if the cancer has metastasized to the liver), tumor ablation, tumor embolization, colon stenting, colorectal surgery, colostomy (e.g., discharge colostomy), and immunotherapy (e.g., pembrolizumab).

Those skilled in the art will appreciate that the colorectal cancer treatments provided herein may be used, for example, as determined by a medical professional, alone or in any combination, in any order, regimen and/or therapeutic schedule. Those skilled in the art will further appreciate that advanced treatment options may be appropriate for early stage cancers in subjects who have previously suffered from colorectal cancer or cancer, for example, subjects who are diagnosed as having recurrent colorectal cancer.

In some embodiments, the methods and compositions for colorectal cancer screening provided herein may provide information for treatment and/or payment decisions and/or actions (e.g., reimbursement or reduction of cost of health care, such as screening or treatment), for example, by individuals, health care facilities, health care professionals, health insurance providers, government agencies, or other parties interested in the cost of health care.

In some embodiments, the colorectal cancer screening methods and compositions provided herein may provide information for decision making regarding whether or not health insurance providers reimburse (or do not reimburse) a healthcare cost recipient or payer, e.g., for (1) self-performed screening (e.g., reimbursement for screening not otherwise available, available only for periodic/regular screening, or available only for temporary and/or additional screening); and/or for (2) treatment, including initiation, maintenance, and/or alteration of therapy, e.g., based on screening results. For example, in some embodiments, the colorectal cancer screening methods and compositions provided herein are used as a basis for, to contribute to, or to support, a determination as to whether a reimbursement or cost reduction will be provided to a healthcare cost recipient or payer. In some cases, a party seeking reimbursement or cost reduction may provide results of a screening performed in accordance with this specification in conjunction with a request for such reimbursement or cost reduction for a health care cost. In some cases, a party making a determination as to whether or not to provide reimbursement or cost reduction for a health care cost will reach a determination based in whole or in part on receipt and/or review of results of a screening performed in accordance with this specification.

For the avoidance of doubt, those skilled in the art will appreciate from the present disclosure that the methods and compositions for diagnosing colorectal cancer of the present disclosure are at least for use in vitro. Accordingly, all aspects and embodiments of the present disclosure may be performed and/or used at least in vitro.

Kits

The present disclosure includes, among other things, kits that include one or more compositions as encompassed by the wording of the claims for use in screening for colorectal cancer as provided herein, optionally in combination with instructions for use thereof in screening for colorectal cancer.

A colorectal cancer screening kit may include one or more of: one or more oligonucleotide primers (e.g., one or more oligonucleotide primer pairs, e.g., as found in Table 13), one or more SERMs, one or more qPCR reagents (e.g., reagents sufficient for a complete qPCR reaction mixture, including, but not limited to, dNTPs and polymerase), and instructions for use of one or more components of the colorectal cancer screening kit.

A colorectal cancer screening kit may include one or more of: one or more oligonucleotide primers (e.g., one or more oligonucleotide primer pairs, e.g., as found in Table 13), one or more bisulfite reagents, one or more qPCR reagents (e.g., reagents sufficient for a complete qPCR reaction mixture, including, but not limited to, dNTPs and polymerase), and instructions for use of one or more components of the colorectal cancer screening kit.

A kit of the present disclosure includes at least one oligonucleotide primer pair for amplification of a methylation and/or DMR locus as disclosed herein.

In some cases, a kit of the present disclosure includes one or more oligonucleotide primer pairs for amplification of one or more methylation loci of the present disclosure. In some cases, a kit of the present disclosure includes one or more oligonucleotide primer pairs for amplification of one or more methylation loci that are or include all or a portion of one or more genes provided in Table 1. In some particular cases, a kit of the present disclosure includes oligonucleotide primer pairs for a plurality of methylation loci that are or include, each, all or a portion of a gene identified in Table 1, the plurality of methylation loci including, for example, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, or 16 methylation loci, for example, as provided in any of Tables 1 to 6.

In some cases, a kit of the present disclosure includes one or more oligonucleotide primer pairs for amplification of one or more DMRs of the present disclosure. In some cases, a kit of the present disclosure includes one or more oligonucleotide primer pairs for amplification of one or more<d>M<r>that are, include all or a portion of, or are within a gene identified in Table 1.

A kit of the present disclosure includes oligonucleotide primer pairs for a plurality of DMRs each of which is, includes all or a portion of, or is within a gene identified in Table 1, e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, or 16 DMRs, e.g., according to any one of Tables 1 to 6.

In some cases, a kit of the present disclosure includes one or more oligonucleotide primer pairs for amplification of one or more DMRs of Table 7. In some particular cases, a kit of the present disclosure includes oligonucleotide primer pairs for a plurality of DMRs of Table 7, the plurality of DMRs including, for example, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, or 28 DMRs of Table 7, for example, as provided in any of Tables 8 to 12.

A kit of the present disclosure includes one or more oligonucleotide primer pairs provided in Table 13. Those skilled in the art will appreciate that the oligonucleotide primer pairs provided in Table 13 may be provided in any combination of one or more oligonucleotide primer pairs, for example, in a combination as provided in any one of Tables 1-12.

In various particular embodiments, a kit of the present disclosure does not include oligonucleotide primer pairs that amplify all or a portion of one or more of FGF14, ZNF471, PDGFD, and ALK.

A kit of the present disclosure may further include one or more SERMs individually or in a single solution. In various embodiments, one or more SERMs are selected from the set of SERMs including Acyl, Hin6l, HpyCH4lV, and Hpall (e.g., such that the kit includes Acyl, Hin6l, and HpyCH4lV, either individually or in a single solution). In certain embodiments, a kit of the present disclosure includes one or more qPCR reagents (e.g., reagents sufficient for a complete qPCR reaction mixture, including, but not limited to, dNTPs and polymerase).

Examples

The present examples confirm that the present disclosure provides methods and compositions for, among other things, screening for and treating colorectal cancer. The present examples further demonstrate that the compositions and methods provided herein provide a remarkably high degree of sensitivity and specificity in screening and/or treating colorectal cancer. Also provided are clinical studies comparing biomarker methylation in samples from subjects diagnosed with colorectal cancer and biomarker methylation in samples from control subjects, further demonstrating colorectal cancer screening including the methods and/or compositions of the present disclosure. Unless specifically stated otherwise, the samples in the present examples are from humans or of human origin. With the exception of Example 1, all experiments were performed using plasma samples.

Example 1. Identification of methylation biomarkers associated with colorectal cancer

The present example includes the identification of CpG loci that are hypermethylated in one or more of colon cancer and rectal cancer compared to healthy controls. In particular, experiments in the present example examined CpG methylation in samples from (i) colon cancers from 341 subjects previously diagnosed with colon cancer, subjects who had not been previously treated with chemotherapy or radiotherapy; (ii) rectal cancers from 118 subjects previously diagnosed with rectal cancer, subjects who had not been previously treated with chemotherapy or radiotherapy; (iii) colons from 40 healthy control subjects who were not diagnosed with colorectal cancer; and (iv) leukocytes from 10 healthy control subjects who were not diagnosed with colorectal cancer. The tissue samples were from fresh frozen tissue.

Samples were analyzed for DNA methylation using a global methylomics analysis platform (Infinium HumanMethylation450 (HM450) bead array). The Infinium HumanMethylation450 array assesses the methylation status of >450,000 CpGs located across the entire genome. DNA methylation profiles were obtained from all tissue samples.

CpG methylation sites for which the methylation status did not differ substantially between colorectal cancer and healthy controls were identified and eliminated from consideration (mean b value < 0.25 and b value > 0.3 in no more than five samples across the entire set). This filtering produced a list of CpG methylation sites for which the methylation status differed substantially between colorectal cancer and healthy controls. The resulting set of CpG methylation sites was then further filtered by excluding CpG methylation sites with a mean b value difference equal to or less than 0.1, yielding 253 CpG methylation sites. Each of the 253 CpG methylation sites was associated with a hypermethylated status in the colorectal cancer state compared to controls. Thus, the present example generated a set of 253 individual CpG methylation sites that are methylation biomarkers for colorectal cancer. The 253 methylation biomarkers represent a plurality of DMRs together found within 36 genes, i.e., within 36 methylation loci. Each of the 36 DMRs is hypermethylated in colorectal cancer compared to healthy controls.

Example 2. Development of cell-free DNA assay to detect methylation biomarkers by MSRE-qPCR

This example develops an assay to determine the methylation status of colorectal cancer methylation biomarkers based on circulating cell-free DNA (cfDNA). cfDNA is incomplete and fragmented, and the mechanism by which cfDNA is transmitted from cancer cells to the blood (as a portion termed circulating tumor DNA) is unknown. At least because all 253 methylation biomarkers in Example 1 were identified from tissue samples, it was not known prior to the experiments in this example whether the identified colorectal cancer methylation biomarkers could be sufficiently analyzed from cfDNA to satisfactorily capture the portion of cfDNA that identifies subjects or samples for colorectal cancer.

As a critical step toward determining whether the colorectal cancer methylation biomarkers identified in Example 1 could be sufficiently analyzed from ctDNA to satisfactorily capture the portion of ctDNA that allows identification of subjects or samples for colorectal cancer, a sensitive assay for screening these biomarkers was developed. In particular, a methylation-sensitive restriction enzyme (MSRE) qPCR methodology was developed. The MSRE-qPCR methodology was developed to measure methylation of DMRs covering CpG sites identified in blood samples, in particular in cell-free DNA (cfDNA) from tumors present in blood.

The development of the MSRE-qPCR methodology was significant, at least in part, because analyzing tumor tissue-derived CpG methylation biomarkers using ctDNA analysis is difficult due to the low concentration of circulating tumor-derived DNA in blood (0.1-1%) compared to the non-tumor DNA background of the sample. Thus, while it is generally preferred to develop biomarker assays that rely on easily obtained samples such as blood, urine, or stool, the use of blood for the analysis of tumor-derived methylation biomarkers is difficult. Thus, even after the identification of methylation biomarkers characteristic of colorectal cancer in tissue, as discussed above, it cannot be predicted whether the fragmented and poorly understood nature of ctDNA will allow successful screening using tissue-identified methylation biomarkers.

MSRE-qPCR requires the design of oligonucleotide primers (MSRE-qPCR oligonucleotide primer pairs) that amplify loci each including at least one colorectal cancer MSRE cleavage site (i.e., an MSRE cleavage site that covers at least one colorectal cancer methylation biomarker site, such that cleavage of the MSRE cleavage site is permitted in nucleic acid molecules in which all of the at least one colorectal cancer methylation biomarker site is unmethylated and is blocked in nucleic acid molecules in which at least one of the at least one colorectal cancer methylation biomarker site is methylated). MSRE-qPCR assays may use multiple restriction enzymes to enhance the range of colorectal cancer methylation biomarker sites that can be assayed by a single MSRE-qPCR reaction, as a single MSRE is unlikely to cleave sites that together include all of the methylation biomarker sites of interest. The MSRE-qPCR assays in the present examples use the Acyl MSREs Hin6l and HpyCH4lV, which together are found to provide sufficient coverage. An exemplary schematic workflow for MSRE-qPCR is provided in Figure 1. As performed in the present examples, circulating cell-free tumor DNA was extracted from subject blood (typically approximately a 4 mL plasma sample) using the QIAamp MinElute ccfDNA Kit according to the manufacturer's protocol (QIAamp MinElute ccfDNA Handbook 08/2018, Qiagene). As shown in Figure 1, isolated lncDNA was divided into two aliquots, a first such aliquot is used in a qPCR quality control analysis and a second such aliquot is used in MSRE-qPCR.

For MSRE-qPCR, 2/3 of the eluted volume cfDNA was digested with MSRE. Since unmethylated DNA is selectively cleaved, contacting cfDNA with MSRE enriches the sample for methylation-derived signal; methylated DNA remains intact and quantifiable. The remaining 1/3 of the eluted volume cfDNA was used for qPCR using the MSRE-qPCR oligonucleotide primers to confirm that amplicons were successfully amplified from cfDNA, which amplification confirms that template is present, thus providing technical quality control.

As applied herein, MSRE-qPCR oligonucleotide primer pairs were successfully developed for amplification of DMRs together including 180 of the 253 CpG methylation biomarker sites identified in Example 1. DMRs typically included 1 to 15 MSRE cleavage sites, MSRE cleavage sites that together covered each of the 180 methylation biomarker sites. As applied herein, the methylation status of six genes (JUB, H19, TBP, TCEB2, SNRPN, IRF4) provided a methylation control, which allowed monitoring of assay robustness and reproducibility.

Example 3. MSRE-qPCR of lcDNA successfully distinguishes subjects based on colorectal cancer status

To examine the clinical diagnostic and prognostic power of identified methylation biomarkers, DMRs amplified by MSRE-qPCR oligonucleotide primer pairs covering all 180 methylation biomarker sites, and appropriate controls, were assayed in lncDNA extracted from plasma of human subjects. Subjects were undiagnosed individuals seeking, or in the process of seeking, a diagnosis for possible colorectal cancer such that methylation biomarker analysis could be performed prior to a traditional diagnostic test for colorectal cancer and then compared to a subsequent traditional diagnosis. In particular, cfDNA samples were collected from undiagnosed individuals seeking, or in the process of seeking, a diagnosis for possible colorectal cancer at screening centers and oncology clinics in Spain and the United States between 2017 and 2018. A first subject group included 70 such individuals (see description of the first subject group in Figure 2), and a second subject group included 63 such individuals (see description of the second subject group in Figure 3). Initial results based on MSRE-qPCR analysis of a small panel of tested DMRs for the genes shown in Table 14 in the second subject group provided proof of concept for the diagnosis of colorectal cancer: the results demonstrated an overall diagnostic sensitivity of 80% for colorectal cancer, with a diagnostic sensitivity of up to 75% for early localized colorectal cancer, and a specificity of 90% (Figure 4). The representative DMR proof-of-concept panel performed similarly and/or statistically equally well for proximal and distal cancers (Figure 4). The DMR proof-of-concept panel also performed similarly and/or statistically equally well for localized and advanced cancer (Figure 4). Furthermore, MSRE-qPCR analysis of methylation of MSRE-qPCR control genes and undigested DNA controls showed high technical reliability of the developed MSRE-qPCR assays in measuring colorectal cancer biomarker methylation status in plasma ctDNA.

Figures 5-9 show the association of colorectal cancer DMR methylation status with colorectal cancer. Results are presented as the MSRE-qPCR Ct value subtracted from 45 (i.e., 45 - Ct value) for presentation purposes. The results demonstrate the surprisingly high predictive power of individual colorectal cancer methylation biomarkers, or as few as three individual colorectal cancer methylation biomarkers, of the present disclosure for colorectal cancer, for example, for use in determining colorectal cancer screening in a subject.

Table 14. Proof-of-concept DMR panel

Example 4. Further validation of methylation biomarkers using MSRE-qPCR

To verify the predictive power of methylation biomarker DMR for colorectal cancer, data derived from MSRE-qPCR analysis of samples from the 133 subjects in the first and second subject groups identified in Example 3 were further analyzed (see Figures 2 and 3). Monte-Carlo cross-validation over 50 runs was used and a random forest algorithm was used for feature classification and markers with VIP >2 were used to build a support vector machine (SVM) algorithm-based classification model. This analysis identified several subsets of markers (2, 3, 5, 8, 15, 28 as described in Tables 7-12) that gave good prediction in the SVM model.

All models (panels of 2, 3, 5, 8, 15, and 28 colorectal cancer DMRs) were applied to cfDNA extracted from plasma of a third subject group. The third subject group included 82 subjects who either had a previously confirmed diagnosis of colorectal cancer or were control subjects known not to have colorectal cancer (including the control group subjects who had hyperplastic polyps and/or non-advanced adenoma, but not colorectal cancer), based on colonoscopy screening. All 82 subjects were subjects attending colorectal cancer screening and oncology units in Spain and the United States. An additional description of the third subject group is shown in Figure 10.

Oligonucleotide primer pairs (Table 13) for amplification of all 28 DMRs in MSRE-qPCR cover at least one MSRE cleavage site, typically 3 to 15 MSRE cleavage sites. MSRE-qPCR was performed according to the methodology described in Example 2.

Notwithstanding the sufficiency and utility of all of the panels tested for colorectal cancer screening, those skilled in the art will appreciate that the 28 DMR panel provided increased sensitivity and comparable specificity compared to all other <d>M<r> panels listed in Table 15. For the avoidance of doubt, all of the panels tested, e.g., as described in Tables 7-14, are individually sufficient (e.g., for both sensitivity and specificity), and useful, for clinical colorectal cancer screening. Analysis of the third group of subjects using the 28 d Mr colorectal cancer panel showed an overall sensitivity for the diagnosis of colorectal cancer of 79%, with a sensitivity of 75% for localized (early) cancer and a sensitivity of 84% for advanced cancer. The data also revealed a specificity of 87% at a U<c>of 82% (Figure 11). Figure 11 provides a ROC curve analysis of the data from the second validation set based on a panel of 28 markers identified using the SVM model.

Thus, evaluation of the performance of the 28-DMR colorectal cancer panel and subsets thereof revealed that both the full panel and each of the various sets of 2, 3, 5, 8, and 15 of the 28 DMR colorectal cancer are individually sufficient for clinical colorectal cancer screening (see Tables 7-14). For example, to highlight just one example, the 3-DMR subset (Table 9) achieved good separation of colorectal cancer subjects from control subjects, demonstrating sufficient performance for clinical colorectal cancer screening, at least in part as demonstrated by the determined sensitivity of 60% and specificity of 87% (Table 15).

Features of the SVM model are described in Table 16. The input SVM support vectors and their coefficient (weight) values are given in Table 17 (due to the size of Table 17, Table 17 is presented in several chunks, with coefficients and gene names repeated in each chunk for reference). For prediction purposes, the information provided was used in combination with the predict() function in the R package (see Hypertext Transfer Protocol Secure (HTTPS)://cran.r-project.org/web/packages/e1071/index.html).

Table 15. Accuracy metrics for the application of the 28-DMR colorectal cancer panel and subsets thereof to the third group of subjects

Table 16. SVM model input characteristics

Table 17. SVM Vectors

Table 17, continued. SVM Vectors

Table 17, continued. SVM Vectors

Table 17, continued. SVM Vectors

Table 17, continued. SVM Vectors

Table 17, continued. SVM Vectors

Table 17, continued. SVM Vectors

Table 17, continued. SVM Vectors

Table 17, continued. SVM Vectors

Table 17, continued. SVM Vectors

Table 17, continued. SVM Vectors

Table 17, continued. SVM Vectors

Example 5. Various individual methylation biomarkers are each highly informative

Evaluation of the performance of individual colorectal cancer DMRs from the panel of 28 colorectal cancer DMRs revealed that several individual colorectal cancer DMRs are sufficient for colorectal cancer screening (see Figures 12-19). For selected colorectal cancer DMRs, Figures 12-19 show the methylation status of the indicated DMR in colorectal cancer samples and control samples. Results are presented as the MSRE-qPCR Ct value subtracted from 45 (i.e., 45 - Ct value) for presentation purposes. The data provided in this example, as well as data provided by the present examples cumulatively (including, for example, Figures 5-9), demonstrate that, for each individual colorectal cancer DMR, the methylation status signal is sufficiently stable across subject groups to enable clinical screening. Thus, the results presented in Figures 12-19 confirm that the colorectal cancer methylation markers provided herein can provide a robust signal for colorectal cancer screening. Furthermore, those skilled in the art will appreciate that the present disclosure provides methylation biomarkers that are independently or individually useful in colorectal cancer screening, and specifically that the methylation biomarkers provided herein are useful both individually and in combination.

Example 6. Validation of markers

Blood plasma samples were used to determine a minimum viable DMR panel for colorectal cancer screening. DMR methylation status was found to be useful in distinguishing colorectal cancer not only from healthy subjects, but also from subjects suffering from other types of cancers (e.g., breast cancer, lung cancer).

Blood plasma samples from 215 subjects were analyzed using MSRE-qPCR and used as a training set to determine a minimum viable DMR panel for colorectal cancer detection. Figure 21 presents a detailed view of the subject cohort used to train an algorithm to detect colorectal cancer. The training set included 93 human subjects who had been diagnosed with colorectal cancer (CRC), 91 subjects who had been diagnosed as healthy, and 31 subjects who had been diagnosed as having non-advanced adenoma (NAA). The NAA+healthy column is the sum of the healthy and NAA columns. For the purpose of calculating specificities, all patients who did not have a diagnosis of colorectal cancer were considered to be controls. Figure 21 also indicates the distribution of colorectal cancer. Colorectal cancer is classified as localized or advanced as determined by histology. The location of colorectal cancer as determined by colonoscopy is found to be either in the proximal or distal part of the colon.

The selected DMRs that showed potential in detecting colorectal cancer were further validated using an independent validation subject set (see Figure 22). Plasma samples were collected from 774 human subjects in Spain, Ukraine, the UK, and the US. Of those 774 subjects, 152 subjects were diagnosed with colorectal cancer (CRC). The control group included 622 subjects. 148 of the control subjects had non-advanced adenoma, and 52 of the control subjects had cancer other than CRC (i.e., breast cancer or lung cancer). Figure 22 displays the number of men and women in each group, age range, and total number of subjects. For those with cancer (i.e., colorectal, breast, or lung cancer), the cancer is classified as localized or advanced.

A random forest feature selection algorithm was implemented for feature classification. The algorithm used Monte-Carlo cross-validation over 50 subset iterations with the training set from Figure 21 to rank the previously selected markers based on their variance of importance (VIP) of occurrence over the 50 iterations. Markers with VIP > 2 were further used for the construction of the support vector machine algorithm with the training set.

All 3-DMR (Figure 23), 5-DMR (Figure 24), and 6-DMR (Figure 25) panels were found to perform well in assessing the colorectal cancer status of subjects in the validation set (Figure 22). Tables 18, 19, and 20 (shown below) identify the markers included in each of the 3-, 5-, and 6-marker panels, respectively.

Table 18. 3 DMR panel.

Table 19. 5 DMR panel.

Table 20. 6 DMR panel.

In addition, Table 21 (below) shows the accuracy, sensitivity, specificity, and AUC of each of the 3 DMR (Table 18), 5 DMR (Table 19), and 6 DMR (Table 20) panels as presented above.

Table 21. ROC curve analysis of each model

The best performing algorithm used the 6 markers in Table 20 and resulted in 69% of colorectal cancer cases being detected with a specificity of 87% with an overall AUC of 86%. Additionally, both the 3-marker and 5-marker panels performed well in classifying colorectal cancer. In the 3-marker panel, 58% of colorectal cancer cases were detected with a specificity of 89% and an AUC of 84.5%.

These findings are particularly noteworthy as high specificity was maintained even though subjects with cancer diagnoses other than colorectal cancer were included in the control group. This finding indicates that the markers in question are not generally indicative of cancer, but are specifically and surprisingly important for detecting colorectal cancer.

The present disclosure includes combinations of DMRs where each of the DMRs is, includes all of, includes a portion of, or is present in a gene identified in Table 22.

The present disclosure includes combinations of DMRs where each of the DMRs is, includes all of, includes a portion of, or is present in a gene identified in Table 23.

The present disclosure includes combinations of DMRs wherein each of the DMRs is, includes all of, includes a portion of, or is present in a gene identified in Table 24. In some particular embodiments, a colorectal cancer methylation biomarker includes two DMRs, each of which is, includes all of, includes a portion of, or is present in a different gene identified in Table 22. A colorectal cancer methylation biomarker includes four DMRs, each of which is, includes all of, includes a portion of, or is present in a different gene identified in Table 23. A colorectal cancer methylation biomarker includes five DMRs, each of which is, includes all of, includes a portion of, or is present in a different gene identified in Table 24.

A colorectal cancer methylation biomarker includes two or more DMRs that include all of, include a portion of, or are present in the same gene from Table 22. In various embodiments, a colorectal cancer methylation biomarker includes two or more DMRs that include all of, include a portion of, or are present in the same gene from Table A colorectal cancer methylation biomarker includes two or more DMRs that include all of, include a portion of, or are present in the same gene from Table 24.

Table 22. DMR gene panel from Table 18.

Table 23. DMR gene panel from Table 19.

Table 24. DMR gene panel from Table 20

Example 7. Various individual methylation biomarkers are each highly informative

Evaluation of the performance of individual colorectal cancer DMRs from the colorectal cancer DMR panel (e.g., as set forth in Example 6) revealed that several individual colorectal cancer DMRs are sufficient for colorectal cancer screening not only of healthy individuals but also of individuals suffering from other cancers. A univariate analysis across the methylation status of each of the methylation markers as shown in Table 25 below shows several markers with high individual precision as indicated by p-values that are less than 0.001.

Table 25. P values of t test between CRC and control groups in the validation set

For the selected colorectal cancer DMRs from Table 25, Figures 26-31 additionally show the methylation status of the indicated DMR in colorectal cancer samples and control samples (i.e., from the validation set in Figure 22). In this case, the control samples comprise healthy subjects, subjects who have non-advanced adenomas, subjects who have breast cancer, and subjects who have lung cancer (see Figure 22). The results are presented as the MSRE-qPCR Ct value subtracted from 45 (i.e., 45 - Ct value) for presentation purposes. The data provided in this example, as well as data provided by the present examples cumulatively (including, for example, Figures 23-25), demonstrate that, for each individual colorectal cancer DMR, the methylation status signal is sufficiently and surprisingly stable across subject groups to allow for clinical screening, particularly for distinguishing colorectal cancer from other forms of cancer. Thus, the results presented in Figures 23-25 further confirm that the colorectal cancer methylation markers provided herein can provide a robust signal for colorectal cancer screening. Furthermore, those skilled in the art will appreciate that the present disclosure provides that these methylation biomarkers are individually useful in colorectal cancer screening, and specifically that the methylation biomarkers provided herein are useful both individually and in combination.

Claims (21)

1. In vitro method for screening for colorectal cancer in a subject, the method comprising: - determine a methylation status for each of the following, in a DNA sample from a subject: (a) a methylation locus within the ZNF132 gene; (b) a first methylation locus within the ADAMTS2 gene; and (c) a second methylation locus within the ADAMTS2 gene; and - compare the data obtained with reference values obtained from healthy individuals, - diagnose colorectal cancer in the subject if hypermethylation of the loci is detected, compared to the reference sample. 2. The method of claim 1, further comprising determining a methylation status for each of the following, in a DNA sample from a subject: (d) a methylation locus within the ZNF542 gene; and (e) a methylation locus within the LONRF2 gene. 3. The method of claims 1 to 2, further comprising determining a methylation status for a methylation locus within the ZNF492 gene in a DNA sample from a subject. 4. The method according to claims 1 to 3, wherein the methylation locus within the ZNF132 gene comprises ZNF132 '415 (SEQ ID NO: 40). 5. The method according to claims 1 to 4, wherein the first methylation locus within the ADAMTS2 gene comprises ADAMTS2 '254 (SEQ ID NO: 21). 6. The method of claims 1 to 5, wherein the second methylation locus within the ADAMTS2 gene comprises ADAMTS2 '284 (SEQ ID NO: 22). 7. The method of claims 2 to 6, wherein the methylation locus within the ZNF542 gene comprises ZNF542 '502 (SEQ ID NO: 35). 8. The method of claims 2 to 7, wherein the methylation locus within the LONRF2 gene comprises LONRF2 '281 (SEQ ID NO: 19). 9. The method of claims 3 to 8, wherein the methylation locus within the ZNF492 gene comprises ZNF492 '069 (SEQ ID NO: 42). 10. Method according to any one of claims 1 to 9, wherein the DNA is isolated from blood or plasma of the human subject. 11. The method of claims 1 to 10, wherein the DNA is cell-free DNA of the human subject. 12. Method according to claims 1 to 11, wherein methylation status is determined using quantitative polymerase chain reaction (qPCR). 13. Kit comprising: (a) a pair of oligonucleotide primers for amplification of a methylation locus within the ZNF132 gene; (b) a pair of oligonucleotide primers for the amplification of a first methylation locus within the<a>D<a>MTS2 gene; and (c) an oligonucleotide primer pair for amplification of a second methylation locus within the ADAMTS2 gene. The kit optionally also includes: (d) at least one methylation-specific restriction enzyme and/or a bisulfite reagent (e) a polymerase. 14. Kit according to claim 13, further comprising: (f) a pair of oligonucleotide primers for the amplification of a methylation locus within the ZNF542 gene; and (g) A pair of oligonucleotide primers for amplification of a methylation locus within the LONRF2 gene. 15. Kit according to claims 13 to 14, further comprising: (h) a pair of oligonucleotide primers for amplification of a methylation locus within the ZNF492 gene. 16. Kit according to claims 13 to 15, wherein (a) is an oligonucleotide primer pair for the amplification of ZNF132 '415 (primer pair Eq ID NO: 91 and SEQ ID NO: 92). 17. Kit according to claims 13 to 16, wherein (b) is a pair of oligonucleotide primers for the amplification of ADAMTS2 '254 (primer pair SEQ ID NO: 53 and SEQ ID NO: 54). 18. Kit according to claims 13 to 17, wherein (c) is a pair of oligonucleotide primers for the amplification of ADAMTS2 '284 (primer pair SEQ ID NO: 55 and SEQ ID NO: 56). 19. Kit according to claims 14 to 18, wherein (f) is an oligonucleotide primer pair for the amplification of ZNF542 '502 (primer pair S<e>Q ID NO: 81 and SEQ ID NO: 82). 20. Kit according to claims 14 to 19, wherein (g) is an oligonucleotide primer pair for the amplification of LONRF2 '281 (primer pair SEQ ID NO: 49 and SEQ ID NO: 50). 21. Kit according to claims 15 to 20, wherein (h) is an oligonucleotide primer pair for the amplification of ZNF492 '069 (primer pair s Eq ID NO: 95 and SEQ ID NO: 96).